Add files using upload-large-folder tool

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-410/trainer_state.json

@@ -0,0 +1,648 @@
+{
+  "best_metric": 2.5317564010620117,
+  "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
+  "epoch": 5.466666666666667,
+  "eval_steps": 10,
+  "global_step": 410,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.4347652792930603,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 2.4954,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 2.556234359741211,
+      "eval_runtime": 43.818,
+      "eval_samples_per_second": 22.822,
+      "eval_steps_per_second": 2.853,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.40230727195739746,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 2.5574,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 2.552377462387085,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3980488181114197,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 2.4669,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 2.549164056777954,
+      "eval_runtime": 43.8389,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.4006142020225525,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 2.5199,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 2.546046495437622,
+      "eval_runtime": 43.8456,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.4202616512775421,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 2.5619,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 2.5431504249572754,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3871513307094574,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 2.5057,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 2.5413730144500732,
+      "eval_runtime": 43.8646,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.36390039324760437,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 2.4606,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 2.5389301776885986,
+      "eval_runtime": 43.8837,
+      "eval_samples_per_second": 22.788,
+      "eval_steps_per_second": 2.848,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.4081075191497803,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 2.4696,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 2.5368435382843018,
+      "eval_runtime": 43.8696,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.5448070764541626,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 2.4258,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 2.538212776184082,
+      "eval_runtime": 43.8585,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.7155500650405884,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 2.4865,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 2.540060043334961,
+      "eval_runtime": 43.8337,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.7326843738555908,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 2.4391,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 2.5385019779205322,
+      "eval_runtime": 43.8789,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.8026068806648254,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 2.4001,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 2.5356342792510986,
+      "eval_runtime": 43.8699,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.8492558598518372,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 2.387,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 2.5329699516296387,
+      "eval_runtime": 43.8654,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 1.1200364828109741,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 2.3817,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 2.5319204330444336,
+      "eval_runtime": 43.847,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.9766451120376587,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 2.4193,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 2.5317564010620117,
+      "eval_runtime": 43.8504,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 1.0703226327896118,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 2.3341,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 2.5564167499542236,
+      "eval_runtime": 43.8299,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.3115178346633911,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 2.2182,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 2.5810468196868896,
+      "eval_runtime": 43.8366,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.4998687505722046,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 2.2379,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 2.580641269683838,
+      "eval_runtime": 43.8362,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.6269217729568481,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 2.2346,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 2.572070360183716,
+      "eval_runtime": 43.8376,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.5595163106918335,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 2.225,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 2.574326276779175,
+      "eval_runtime": 43.8537,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.673547387123108,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 2.2471,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 2.5765159130096436,
+      "eval_runtime": 43.8369,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 1.5295490026474,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 2.204,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 2.5766921043395996,
+      "eval_runtime": 43.8443,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 1.6709380149841309,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 2.1753,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 2.602360248565674,
+      "eval_runtime": 43.8576,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 2.053478240966797,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 2.0405,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 2.6636874675750732,
+      "eval_runtime": 43.8509,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.8616771697998047,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 2.0265,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 2.6536307334899902,
+      "eval_runtime": 43.8433,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 2.1498146057128906,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 2.1386,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 2.658257246017456,
+      "eval_runtime": 43.8516,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.851,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 2.203857660293579,
+      "learning_rate": 4.8e-05,
+      "loss": 2.0367,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 2.658139228820801,
+      "eval_runtime": 43.8709,
+      "eval_samples_per_second": 22.794,
+      "eval_steps_per_second": 2.849,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 2.0805578231811523,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 2.0226,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 2.646563768386841,
+      "eval_runtime": 43.8726,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 2.27193546295166,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 2.1099,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 2.6486735343933105,
+      "eval_runtime": 43.881,
+      "eval_samples_per_second": 22.789,
+      "eval_steps_per_second": 2.849,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 2.0627055168151855,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 2.0996,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 2.644541025161743,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 2.6526894569396973,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.8896,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 2.7607998847961426,
+      "eval_runtime": 43.8953,
+      "eval_samples_per_second": 22.781,
+      "eval_steps_per_second": 2.848,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 2.813822031021118,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.8568,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 2.7357044219970703,
+      "eval_runtime": 43.8795,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 3.134248733520508,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.9636,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 2.742431640625,
+      "eval_runtime": 43.8639,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 2.727226495742798,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.9148,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 2.7314682006835938,
+      "eval_runtime": 43.852,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.85,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 2.768984079360962,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.9134,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 2.7299180030822754,
+      "eval_runtime": 43.8498,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 350
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 3.0203487873077393,
+      "learning_rate": 3.733333333333334e-05,
+      "loss": 1.9445,
+      "step": 360
+    },
+    {
+      "epoch": 4.8,
+      "eval_loss": 2.7333309650421143,
+      "eval_runtime": 43.8634,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 360
+    },
+    {
+      "epoch": 4.933333333333334,
+      "grad_norm": 2.721759080886841,
+      "learning_rate": 3.614814814814815e-05,
+      "loss": 1.9199,
+      "step": 370
+    },
+    {
+      "epoch": 4.933333333333334,
+      "eval_loss": 2.7230074405670166,
+      "eval_runtime": 43.8351,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 370
+    },
+    {
+      "epoch": 5.066666666666666,
+      "grad_norm": 2.812037467956543,
+      "learning_rate": 3.4962962962962965e-05,
+      "loss": 1.9396,
+      "step": 380
+    },
+    {
+      "epoch": 5.066666666666666,
+      "eval_loss": 2.7738075256347656,
+      "eval_runtime": 43.8405,
+      "eval_samples_per_second": 22.81,
+      "eval_steps_per_second": 2.851,
+      "step": 380
+    },
+    {
+      "epoch": 5.2,
+      "grad_norm": 3.347679376602173,
+      "learning_rate": 3.377777777777778e-05,
+      "loss": 1.8374,
+      "step": 390
+    },
+    {
+      "epoch": 5.2,
+      "eval_loss": 2.830467700958252,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 390
+    },
+    {
+      "epoch": 5.333333333333333,
+      "grad_norm": 3.1343460083007812,
+      "learning_rate": 3.259259259259259e-05,
+      "loss": 1.7472,
+      "step": 400
+    },
+    {
+      "epoch": 5.333333333333333,
+      "eval_loss": 2.8105757236480713,
+      "eval_runtime": 43.9522,
+      "eval_samples_per_second": 22.752,
+      "eval_steps_per_second": 2.844,
+      "step": 400
+    },
+    {
+      "epoch": 5.466666666666667,
+      "grad_norm": 3.431727170944214,
+      "learning_rate": 3.140740740740741e-05,
+      "loss": 1.8274,
+      "step": 410
+    },
+    {
+      "epoch": 5.466666666666667,
+      "eval_loss": 2.816023826599121,
+      "eval_runtime": 43.9615,
+      "eval_samples_per_second": 22.747,
+      "eval_steps_per_second": 2.843,
+      "step": 410
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 6.71828951433216e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-420/README.md

@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-420/adapter_config.json

@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "dense_h_to_4h",
+    "query_key_value",
+    "dense",
+    "dense_4h_to_h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-420/trainer_state.json

@@ -0,0 +1,663 @@
+{
+  "best_metric": 2.5317564010620117,
+  "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
+  "epoch": 5.6,
+  "eval_steps": 10,
+  "global_step": 420,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.4347652792930603,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 2.4954,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 2.556234359741211,
+      "eval_runtime": 43.818,
+      "eval_samples_per_second": 22.822,
+      "eval_steps_per_second": 2.853,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.40230727195739746,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 2.5574,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 2.552377462387085,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3980488181114197,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 2.4669,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 2.549164056777954,
+      "eval_runtime": 43.8389,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.4006142020225525,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 2.5199,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 2.546046495437622,
+      "eval_runtime": 43.8456,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.4202616512775421,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 2.5619,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 2.5431504249572754,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3871513307094574,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 2.5057,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 2.5413730144500732,
+      "eval_runtime": 43.8646,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.36390039324760437,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 2.4606,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 2.5389301776885986,
+      "eval_runtime": 43.8837,
+      "eval_samples_per_second": 22.788,
+      "eval_steps_per_second": 2.848,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.4081075191497803,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 2.4696,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 2.5368435382843018,
+      "eval_runtime": 43.8696,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.5448070764541626,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 2.4258,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 2.538212776184082,
+      "eval_runtime": 43.8585,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.7155500650405884,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 2.4865,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 2.540060043334961,
+      "eval_runtime": 43.8337,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.7326843738555908,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 2.4391,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 2.5385019779205322,
+      "eval_runtime": 43.8789,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.8026068806648254,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 2.4001,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 2.5356342792510986,
+      "eval_runtime": 43.8699,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.8492558598518372,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 2.387,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 2.5329699516296387,
+      "eval_runtime": 43.8654,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 1.1200364828109741,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 2.3817,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 2.5319204330444336,
+      "eval_runtime": 43.847,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.9766451120376587,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 2.4193,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 2.5317564010620117,
+      "eval_runtime": 43.8504,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 1.0703226327896118,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 2.3341,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 2.5564167499542236,
+      "eval_runtime": 43.8299,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.3115178346633911,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 2.2182,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 2.5810468196868896,
+      "eval_runtime": 43.8366,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.4998687505722046,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 2.2379,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 2.580641269683838,
+      "eval_runtime": 43.8362,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.6269217729568481,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 2.2346,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 2.572070360183716,
+      "eval_runtime": 43.8376,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.5595163106918335,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 2.225,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 2.574326276779175,
+      "eval_runtime": 43.8537,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.673547387123108,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 2.2471,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 2.5765159130096436,
+      "eval_runtime": 43.8369,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 1.5295490026474,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 2.204,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 2.5766921043395996,
+      "eval_runtime": 43.8443,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 1.6709380149841309,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 2.1753,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 2.602360248565674,
+      "eval_runtime": 43.8576,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 2.053478240966797,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 2.0405,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 2.6636874675750732,
+      "eval_runtime": 43.8509,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.8616771697998047,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 2.0265,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 2.6536307334899902,
+      "eval_runtime": 43.8433,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 2.1498146057128906,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 2.1386,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 2.658257246017456,
+      "eval_runtime": 43.8516,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.851,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 2.203857660293579,
+      "learning_rate": 4.8e-05,
+      "loss": 2.0367,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 2.658139228820801,
+      "eval_runtime": 43.8709,
+      "eval_samples_per_second": 22.794,
+      "eval_steps_per_second": 2.849,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 2.0805578231811523,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 2.0226,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 2.646563768386841,
+      "eval_runtime": 43.8726,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 2.27193546295166,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 2.1099,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 2.6486735343933105,
+      "eval_runtime": 43.881,
+      "eval_samples_per_second": 22.789,
+      "eval_steps_per_second": 2.849,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 2.0627055168151855,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 2.0996,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 2.644541025161743,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 2.6526894569396973,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.8896,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 2.7607998847961426,
+      "eval_runtime": 43.8953,
+      "eval_samples_per_second": 22.781,
+      "eval_steps_per_second": 2.848,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 2.813822031021118,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.8568,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 2.7357044219970703,
+      "eval_runtime": 43.8795,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 3.134248733520508,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.9636,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 2.742431640625,
+      "eval_runtime": 43.8639,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 2.727226495742798,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.9148,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 2.7314682006835938,
+      "eval_runtime": 43.852,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.85,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 2.768984079360962,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.9134,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 2.7299180030822754,
+      "eval_runtime": 43.8498,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 350
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 3.0203487873077393,
+      "learning_rate": 3.733333333333334e-05,
+      "loss": 1.9445,
+      "step": 360
+    },
+    {
+      "epoch": 4.8,
+      "eval_loss": 2.7333309650421143,
+      "eval_runtime": 43.8634,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 360
+    },
+    {
+      "epoch": 4.933333333333334,
+      "grad_norm": 2.721759080886841,
+      "learning_rate": 3.614814814814815e-05,
+      "loss": 1.9199,
+      "step": 370
+    },
+    {
+      "epoch": 4.933333333333334,
+      "eval_loss": 2.7230074405670166,
+      "eval_runtime": 43.8351,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 370
+    },
+    {
+      "epoch": 5.066666666666666,
+      "grad_norm": 2.812037467956543,
+      "learning_rate": 3.4962962962962965e-05,
+      "loss": 1.9396,
+      "step": 380
+    },
+    {
+      "epoch": 5.066666666666666,
+      "eval_loss": 2.7738075256347656,
+      "eval_runtime": 43.8405,
+      "eval_samples_per_second": 22.81,
+      "eval_steps_per_second": 2.851,
+      "step": 380
+    },
+    {
+      "epoch": 5.2,
+      "grad_norm": 3.347679376602173,
+      "learning_rate": 3.377777777777778e-05,
+      "loss": 1.8374,
+      "step": 390
+    },
+    {
+      "epoch": 5.2,
+      "eval_loss": 2.830467700958252,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 390
+    },
+    {
+      "epoch": 5.333333333333333,
+      "grad_norm": 3.1343460083007812,
+      "learning_rate": 3.259259259259259e-05,
+      "loss": 1.7472,
+      "step": 400
+    },
+    {
+      "epoch": 5.333333333333333,
+      "eval_loss": 2.8105757236480713,
+      "eval_runtime": 43.9522,
+      "eval_samples_per_second": 22.752,
+      "eval_steps_per_second": 2.844,
+      "step": 400
+    },
+    {
+      "epoch": 5.466666666666667,
+      "grad_norm": 3.431727170944214,
+      "learning_rate": 3.140740740740741e-05,
+      "loss": 1.8274,
+      "step": 410
+    },
+    {
+      "epoch": 5.466666666666667,
+      "eval_loss": 2.816023826599121,
+      "eval_runtime": 43.9615,
+      "eval_samples_per_second": 22.747,
+      "eval_steps_per_second": 2.843,
+      "step": 410
+    },
+    {
+      "epoch": 5.6,
+      "grad_norm": 3.4572854042053223,
+      "learning_rate": 3.0222222222222225e-05,
+      "loss": 1.8135,
+      "step": 420
+    },
+    {
+      "epoch": 5.6,
+      "eval_loss": 2.817023992538452,
+      "eval_runtime": 43.9443,
+      "eval_samples_per_second": 22.756,
+      "eval_steps_per_second": 2.845,
+      "step": 420
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 6.88215023419392e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-430/README.md

@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-430/adapter_config.json

@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "dense_h_to_4h",
+    "query_key_value",
+    "dense",
+    "dense_4h_to_h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-430/trainer_state.json

@@ -0,0 +1,678 @@
+{
+  "best_metric": 2.5317564010620117,
+  "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
+  "epoch": 5.733333333333333,
+  "eval_steps": 10,
+  "global_step": 430,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.4347652792930603,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 2.4954,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 2.556234359741211,
+      "eval_runtime": 43.818,
+      "eval_samples_per_second": 22.822,
+      "eval_steps_per_second": 2.853,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.40230727195739746,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 2.5574,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 2.552377462387085,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3980488181114197,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 2.4669,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 2.549164056777954,
+      "eval_runtime": 43.8389,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.4006142020225525,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 2.5199,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 2.546046495437622,
+      "eval_runtime": 43.8456,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.4202616512775421,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 2.5619,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 2.5431504249572754,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3871513307094574,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 2.5057,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 2.5413730144500732,
+      "eval_runtime": 43.8646,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.36390039324760437,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 2.4606,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 2.5389301776885986,
+      "eval_runtime": 43.8837,
+      "eval_samples_per_second": 22.788,
+      "eval_steps_per_second": 2.848,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.4081075191497803,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 2.4696,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 2.5368435382843018,
+      "eval_runtime": 43.8696,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.5448070764541626,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 2.4258,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 2.538212776184082,
+      "eval_runtime": 43.8585,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.7155500650405884,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 2.4865,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 2.540060043334961,
+      "eval_runtime": 43.8337,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.7326843738555908,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 2.4391,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 2.5385019779205322,
+      "eval_runtime": 43.8789,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.8026068806648254,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 2.4001,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 2.5356342792510986,
+      "eval_runtime": 43.8699,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.8492558598518372,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 2.387,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 2.5329699516296387,
+      "eval_runtime": 43.8654,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 1.1200364828109741,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 2.3817,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 2.5319204330444336,
+      "eval_runtime": 43.847,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.9766451120376587,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 2.4193,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 2.5317564010620117,
+      "eval_runtime": 43.8504,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 1.0703226327896118,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 2.3341,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 2.5564167499542236,
+      "eval_runtime": 43.8299,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.3115178346633911,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 2.2182,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 2.5810468196868896,
+      "eval_runtime": 43.8366,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.4998687505722046,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 2.2379,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 2.580641269683838,
+      "eval_runtime": 43.8362,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.6269217729568481,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 2.2346,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 2.572070360183716,
+      "eval_runtime": 43.8376,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.5595163106918335,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 2.225,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 2.574326276779175,
+      "eval_runtime": 43.8537,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.673547387123108,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 2.2471,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 2.5765159130096436,
+      "eval_runtime": 43.8369,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 1.5295490026474,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 2.204,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 2.5766921043395996,
+      "eval_runtime": 43.8443,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 1.6709380149841309,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 2.1753,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 2.602360248565674,
+      "eval_runtime": 43.8576,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 2.053478240966797,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 2.0405,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 2.6636874675750732,
+      "eval_runtime": 43.8509,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.8616771697998047,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 2.0265,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 2.6536307334899902,
+      "eval_runtime": 43.8433,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 2.1498146057128906,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 2.1386,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 2.658257246017456,
+      "eval_runtime": 43.8516,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.851,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 2.203857660293579,
+      "learning_rate": 4.8e-05,
+      "loss": 2.0367,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 2.658139228820801,
+      "eval_runtime": 43.8709,
+      "eval_samples_per_second": 22.794,
+      "eval_steps_per_second": 2.849,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 2.0805578231811523,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 2.0226,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 2.646563768386841,
+      "eval_runtime": 43.8726,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 2.27193546295166,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 2.1099,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 2.6486735343933105,
+      "eval_runtime": 43.881,
+      "eval_samples_per_second": 22.789,
+      "eval_steps_per_second": 2.849,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 2.0627055168151855,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 2.0996,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 2.644541025161743,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 2.6526894569396973,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.8896,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 2.7607998847961426,
+      "eval_runtime": 43.8953,
+      "eval_samples_per_second": 22.781,
+      "eval_steps_per_second": 2.848,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 2.813822031021118,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.8568,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 2.7357044219970703,
+      "eval_runtime": 43.8795,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 3.134248733520508,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.9636,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 2.742431640625,
+      "eval_runtime": 43.8639,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 2.727226495742798,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.9148,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 2.7314682006835938,
+      "eval_runtime": 43.852,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.85,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 2.768984079360962,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.9134,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 2.7299180030822754,
+      "eval_runtime": 43.8498,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 350
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 3.0203487873077393,
+      "learning_rate": 3.733333333333334e-05,
+      "loss": 1.9445,
+      "step": 360
+    },
+    {
+      "epoch": 4.8,
+      "eval_loss": 2.7333309650421143,
+      "eval_runtime": 43.8634,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 360
+    },
+    {
+      "epoch": 4.933333333333334,
+      "grad_norm": 2.721759080886841,
+      "learning_rate": 3.614814814814815e-05,
+      "loss": 1.9199,
+      "step": 370
+    },
+    {
+      "epoch": 4.933333333333334,
+      "eval_loss": 2.7230074405670166,
+      "eval_runtime": 43.8351,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 370
+    },
+    {
+      "epoch": 5.066666666666666,
+      "grad_norm": 2.812037467956543,
+      "learning_rate": 3.4962962962962965e-05,
+      "loss": 1.9396,
+      "step": 380
+    },
+    {
+      "epoch": 5.066666666666666,
+      "eval_loss": 2.7738075256347656,
+      "eval_runtime": 43.8405,
+      "eval_samples_per_second": 22.81,
+      "eval_steps_per_second": 2.851,
+      "step": 380
+    },
+    {
+      "epoch": 5.2,
+      "grad_norm": 3.347679376602173,
+      "learning_rate": 3.377777777777778e-05,
+      "loss": 1.8374,
+      "step": 390
+    },
+    {
+      "epoch": 5.2,
+      "eval_loss": 2.830467700958252,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 390
+    },
+    {
+      "epoch": 5.333333333333333,
+      "grad_norm": 3.1343460083007812,
+      "learning_rate": 3.259259259259259e-05,
+      "loss": 1.7472,
+      "step": 400
+    },
+    {
+      "epoch": 5.333333333333333,
+      "eval_loss": 2.8105757236480713,
+      "eval_runtime": 43.9522,
+      "eval_samples_per_second": 22.752,
+      "eval_steps_per_second": 2.844,
+      "step": 400
+    },
+    {
+      "epoch": 5.466666666666667,
+      "grad_norm": 3.431727170944214,
+      "learning_rate": 3.140740740740741e-05,
+      "loss": 1.8274,
+      "step": 410
+    },
+    {
+      "epoch": 5.466666666666667,
+      "eval_loss": 2.816023826599121,
+      "eval_runtime": 43.9615,
+      "eval_samples_per_second": 22.747,
+      "eval_steps_per_second": 2.843,
+      "step": 410
+    },
+    {
+      "epoch": 5.6,
+      "grad_norm": 3.4572854042053223,
+      "learning_rate": 3.0222222222222225e-05,
+      "loss": 1.8135,
+      "step": 420
+    },
+    {
+      "epoch": 5.6,
+      "eval_loss": 2.817023992538452,
+      "eval_runtime": 43.9443,
+      "eval_samples_per_second": 22.756,
+      "eval_steps_per_second": 2.845,
+      "step": 420
+    },
+    {
+      "epoch": 5.733333333333333,
+      "grad_norm": 3.286614179611206,
+      "learning_rate": 2.9037037037037042e-05,
+      "loss": 1.8312,
+      "step": 430
+    },
+    {
+      "epoch": 5.733333333333333,
+      "eval_loss": 2.813601493835449,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 430
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 7.04601095405568e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-440/README.md

@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-440/adapter_config.json

@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "dense_h_to_4h",
+    "query_key_value",
+    "dense",
+    "dense_4h_to_h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-440/trainer_state.json

@@ -0,0 +1,693 @@
+{
+  "best_metric": 2.5317564010620117,
+  "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
+  "epoch": 5.866666666666667,
+  "eval_steps": 10,
+  "global_step": 440,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.4347652792930603,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 2.4954,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 2.556234359741211,
+      "eval_runtime": 43.818,
+      "eval_samples_per_second": 22.822,
+      "eval_steps_per_second": 2.853,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.40230727195739746,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 2.5574,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 2.552377462387085,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3980488181114197,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 2.4669,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 2.549164056777954,
+      "eval_runtime": 43.8389,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.4006142020225525,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 2.5199,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 2.546046495437622,
+      "eval_runtime": 43.8456,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.4202616512775421,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 2.5619,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 2.5431504249572754,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3871513307094574,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 2.5057,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 2.5413730144500732,
+      "eval_runtime": 43.8646,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.36390039324760437,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 2.4606,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 2.5389301776885986,
+      "eval_runtime": 43.8837,
+      "eval_samples_per_second": 22.788,
+      "eval_steps_per_second": 2.848,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.4081075191497803,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 2.4696,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 2.5368435382843018,
+      "eval_runtime": 43.8696,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.5448070764541626,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 2.4258,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 2.538212776184082,
+      "eval_runtime": 43.8585,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.7155500650405884,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 2.4865,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 2.540060043334961,
+      "eval_runtime": 43.8337,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.7326843738555908,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 2.4391,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 2.5385019779205322,
+      "eval_runtime": 43.8789,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.8026068806648254,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 2.4001,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 2.5356342792510986,
+      "eval_runtime": 43.8699,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.8492558598518372,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 2.387,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 2.5329699516296387,
+      "eval_runtime": 43.8654,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 1.1200364828109741,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 2.3817,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 2.5319204330444336,
+      "eval_runtime": 43.847,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.9766451120376587,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 2.4193,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 2.5317564010620117,
+      "eval_runtime": 43.8504,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 1.0703226327896118,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 2.3341,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 2.5564167499542236,
+      "eval_runtime": 43.8299,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.3115178346633911,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 2.2182,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 2.5810468196868896,
+      "eval_runtime": 43.8366,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.4998687505722046,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 2.2379,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 2.580641269683838,
+      "eval_runtime": 43.8362,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.6269217729568481,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 2.2346,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 2.572070360183716,
+      "eval_runtime": 43.8376,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.5595163106918335,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 2.225,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 2.574326276779175,
+      "eval_runtime": 43.8537,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.673547387123108,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 2.2471,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 2.5765159130096436,
+      "eval_runtime": 43.8369,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 1.5295490026474,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 2.204,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 2.5766921043395996,
+      "eval_runtime": 43.8443,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 1.6709380149841309,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 2.1753,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 2.602360248565674,
+      "eval_runtime": 43.8576,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 2.053478240966797,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 2.0405,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 2.6636874675750732,
+      "eval_runtime": 43.8509,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.8616771697998047,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 2.0265,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 2.6536307334899902,
+      "eval_runtime": 43.8433,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 2.1498146057128906,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 2.1386,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 2.658257246017456,
+      "eval_runtime": 43.8516,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.851,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 2.203857660293579,
+      "learning_rate": 4.8e-05,
+      "loss": 2.0367,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 2.658139228820801,
+      "eval_runtime": 43.8709,
+      "eval_samples_per_second": 22.794,
+      "eval_steps_per_second": 2.849,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 2.0805578231811523,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 2.0226,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 2.646563768386841,
+      "eval_runtime": 43.8726,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 2.27193546295166,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 2.1099,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 2.6486735343933105,
+      "eval_runtime": 43.881,
+      "eval_samples_per_second": 22.789,
+      "eval_steps_per_second": 2.849,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 2.0627055168151855,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 2.0996,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 2.644541025161743,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 2.6526894569396973,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.8896,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 2.7607998847961426,
+      "eval_runtime": 43.8953,
+      "eval_samples_per_second": 22.781,
+      "eval_steps_per_second": 2.848,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 2.813822031021118,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.8568,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 2.7357044219970703,
+      "eval_runtime": 43.8795,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 3.134248733520508,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.9636,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 2.742431640625,
+      "eval_runtime": 43.8639,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 2.727226495742798,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.9148,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 2.7314682006835938,
+      "eval_runtime": 43.852,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.85,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 2.768984079360962,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.9134,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 2.7299180030822754,
+      "eval_runtime": 43.8498,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 350
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 3.0203487873077393,
+      "learning_rate": 3.733333333333334e-05,
+      "loss": 1.9445,
+      "step": 360
+    },
+    {
+      "epoch": 4.8,
+      "eval_loss": 2.7333309650421143,
+      "eval_runtime": 43.8634,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 360
+    },
+    {
+      "epoch": 4.933333333333334,
+      "grad_norm": 2.721759080886841,
+      "learning_rate": 3.614814814814815e-05,
+      "loss": 1.9199,
+      "step": 370
+    },
+    {
+      "epoch": 4.933333333333334,
+      "eval_loss": 2.7230074405670166,
+      "eval_runtime": 43.8351,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 370
+    },
+    {
+      "epoch": 5.066666666666666,
+      "grad_norm": 2.812037467956543,
+      "learning_rate": 3.4962962962962965e-05,
+      "loss": 1.9396,
+      "step": 380
+    },
+    {
+      "epoch": 5.066666666666666,
+      "eval_loss": 2.7738075256347656,
+      "eval_runtime": 43.8405,
+      "eval_samples_per_second": 22.81,
+      "eval_steps_per_second": 2.851,
+      "step": 380
+    },
+    {
+      "epoch": 5.2,
+      "grad_norm": 3.347679376602173,
+      "learning_rate": 3.377777777777778e-05,
+      "loss": 1.8374,
+      "step": 390
+    },
+    {
+      "epoch": 5.2,
+      "eval_loss": 2.830467700958252,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 390
+    },
+    {
+      "epoch": 5.333333333333333,
+      "grad_norm": 3.1343460083007812,
+      "learning_rate": 3.259259259259259e-05,
+      "loss": 1.7472,
+      "step": 400
+    },
+    {
+      "epoch": 5.333333333333333,
+      "eval_loss": 2.8105757236480713,
+      "eval_runtime": 43.9522,
+      "eval_samples_per_second": 22.752,
+      "eval_steps_per_second": 2.844,
+      "step": 400
+    },
+    {
+      "epoch": 5.466666666666667,
+      "grad_norm": 3.431727170944214,
+      "learning_rate": 3.140740740740741e-05,
+      "loss": 1.8274,
+      "step": 410
+    },
+    {
+      "epoch": 5.466666666666667,
+      "eval_loss": 2.816023826599121,
+      "eval_runtime": 43.9615,
+      "eval_samples_per_second": 22.747,
+      "eval_steps_per_second": 2.843,
+      "step": 410
+    },
+    {
+      "epoch": 5.6,
+      "grad_norm": 3.4572854042053223,
+      "learning_rate": 3.0222222222222225e-05,
+      "loss": 1.8135,
+      "step": 420
+    },
+    {
+      "epoch": 5.6,
+      "eval_loss": 2.817023992538452,
+      "eval_runtime": 43.9443,
+      "eval_samples_per_second": 22.756,
+      "eval_steps_per_second": 2.845,
+      "step": 420
+    },
+    {
+      "epoch": 5.733333333333333,
+      "grad_norm": 3.286614179611206,
+      "learning_rate": 2.9037037037037042e-05,
+      "loss": 1.8312,
+      "step": 430
+    },
+    {
+      "epoch": 5.733333333333333,
+      "eval_loss": 2.813601493835449,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 430
+    },
+    {
+      "epoch": 5.866666666666667,
+      "grad_norm": 3.152069568634033,
+      "learning_rate": 2.7851851851851856e-05,
+      "loss": 1.7372,
+      "step": 440
+    },
+    {
+      "epoch": 5.866666666666667,
+      "eval_loss": 2.8068931102752686,
+      "eval_runtime": 43.9514,
+      "eval_samples_per_second": 22.752,
+      "eval_steps_per_second": 2.844,
+      "step": 440
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 7.20987167391744e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-450/README.md

@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-450/adapter_config.json

@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "dense_h_to_4h",
+    "query_key_value",
+    "dense",
+    "dense_4h_to_h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-450/trainer_state.json

@@ -0,0 +1,708 @@
+{
+  "best_metric": 2.5317564010620117,
+  "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
+  "epoch": 6.0,
+  "eval_steps": 10,
+  "global_step": 450,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.4347652792930603,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 2.4954,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 2.556234359741211,
+      "eval_runtime": 43.818,
+      "eval_samples_per_second": 22.822,
+      "eval_steps_per_second": 2.853,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.40230727195739746,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 2.5574,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 2.552377462387085,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3980488181114197,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 2.4669,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 2.549164056777954,
+      "eval_runtime": 43.8389,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.4006142020225525,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 2.5199,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 2.546046495437622,
+      "eval_runtime": 43.8456,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.4202616512775421,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 2.5619,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 2.5431504249572754,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3871513307094574,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 2.5057,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 2.5413730144500732,
+      "eval_runtime": 43.8646,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.36390039324760437,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 2.4606,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 2.5389301776885986,
+      "eval_runtime": 43.8837,
+      "eval_samples_per_second": 22.788,
+      "eval_steps_per_second": 2.848,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.4081075191497803,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 2.4696,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 2.5368435382843018,
+      "eval_runtime": 43.8696,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.5448070764541626,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 2.4258,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 2.538212776184082,
+      "eval_runtime": 43.8585,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.7155500650405884,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 2.4865,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 2.540060043334961,
+      "eval_runtime": 43.8337,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.7326843738555908,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 2.4391,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 2.5385019779205322,
+      "eval_runtime": 43.8789,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.8026068806648254,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 2.4001,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 2.5356342792510986,
+      "eval_runtime": 43.8699,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.8492558598518372,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 2.387,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 2.5329699516296387,
+      "eval_runtime": 43.8654,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 1.1200364828109741,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 2.3817,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 2.5319204330444336,
+      "eval_runtime": 43.847,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.9766451120376587,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 2.4193,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 2.5317564010620117,
+      "eval_runtime": 43.8504,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 1.0703226327896118,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 2.3341,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 2.5564167499542236,
+      "eval_runtime": 43.8299,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.3115178346633911,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 2.2182,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 2.5810468196868896,
+      "eval_runtime": 43.8366,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.4998687505722046,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 2.2379,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 2.580641269683838,
+      "eval_runtime": 43.8362,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.6269217729568481,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 2.2346,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 2.572070360183716,
+      "eval_runtime": 43.8376,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.5595163106918335,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 2.225,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 2.574326276779175,
+      "eval_runtime": 43.8537,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.673547387123108,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 2.2471,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 2.5765159130096436,
+      "eval_runtime": 43.8369,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 1.5295490026474,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 2.204,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 2.5766921043395996,
+      "eval_runtime": 43.8443,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 1.6709380149841309,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 2.1753,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 2.602360248565674,
+      "eval_runtime": 43.8576,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 2.053478240966797,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 2.0405,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 2.6636874675750732,
+      "eval_runtime": 43.8509,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.8616771697998047,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 2.0265,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 2.6536307334899902,
+      "eval_runtime": 43.8433,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 2.1498146057128906,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 2.1386,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 2.658257246017456,
+      "eval_runtime": 43.8516,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.851,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 2.203857660293579,
+      "learning_rate": 4.8e-05,
+      "loss": 2.0367,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 2.658139228820801,
+      "eval_runtime": 43.8709,
+      "eval_samples_per_second": 22.794,
+      "eval_steps_per_second": 2.849,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 2.0805578231811523,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 2.0226,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 2.646563768386841,
+      "eval_runtime": 43.8726,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 2.27193546295166,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 2.1099,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 2.6486735343933105,
+      "eval_runtime": 43.881,
+      "eval_samples_per_second": 22.789,
+      "eval_steps_per_second": 2.849,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 2.0627055168151855,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 2.0996,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 2.644541025161743,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 2.6526894569396973,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.8896,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 2.7607998847961426,
+      "eval_runtime": 43.8953,
+      "eval_samples_per_second": 22.781,
+      "eval_steps_per_second": 2.848,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 2.813822031021118,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.8568,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 2.7357044219970703,
+      "eval_runtime": 43.8795,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 3.134248733520508,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.9636,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 2.742431640625,
+      "eval_runtime": 43.8639,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 2.727226495742798,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.9148,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 2.7314682006835938,
+      "eval_runtime": 43.852,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.85,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 2.768984079360962,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.9134,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 2.7299180030822754,
+      "eval_runtime": 43.8498,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 350
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 3.0203487873077393,
+      "learning_rate": 3.733333333333334e-05,
+      "loss": 1.9445,
+      "step": 360
+    },
+    {
+      "epoch": 4.8,
+      "eval_loss": 2.7333309650421143,
+      "eval_runtime": 43.8634,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 360
+    },
+    {
+      "epoch": 4.933333333333334,
+      "grad_norm": 2.721759080886841,
+      "learning_rate": 3.614814814814815e-05,
+      "loss": 1.9199,
+      "step": 370
+    },
+    {
+      "epoch": 4.933333333333334,
+      "eval_loss": 2.7230074405670166,
+      "eval_runtime": 43.8351,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 370
+    },
+    {
+      "epoch": 5.066666666666666,
+      "grad_norm": 2.812037467956543,
+      "learning_rate": 3.4962962962962965e-05,
+      "loss": 1.9396,
+      "step": 380
+    },
+    {
+      "epoch": 5.066666666666666,
+      "eval_loss": 2.7738075256347656,
+      "eval_runtime": 43.8405,
+      "eval_samples_per_second": 22.81,
+      "eval_steps_per_second": 2.851,
+      "step": 380
+    },
+    {
+      "epoch": 5.2,
+      "grad_norm": 3.347679376602173,
+      "learning_rate": 3.377777777777778e-05,
+      "loss": 1.8374,
+      "step": 390
+    },
+    {
+      "epoch": 5.2,
+      "eval_loss": 2.830467700958252,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 390
+    },
+    {
+      "epoch": 5.333333333333333,
+      "grad_norm": 3.1343460083007812,
+      "learning_rate": 3.259259259259259e-05,
+      "loss": 1.7472,
+      "step": 400
+    },
+    {
+      "epoch": 5.333333333333333,
+      "eval_loss": 2.8105757236480713,
+      "eval_runtime": 43.9522,
+      "eval_samples_per_second": 22.752,
+      "eval_steps_per_second": 2.844,
+      "step": 400
+    },
+    {
+      "epoch": 5.466666666666667,
+      "grad_norm": 3.431727170944214,
+      "learning_rate": 3.140740740740741e-05,
+      "loss": 1.8274,
+      "step": 410
+    },
+    {
+      "epoch": 5.466666666666667,
+      "eval_loss": 2.816023826599121,
+      "eval_runtime": 43.9615,
+      "eval_samples_per_second": 22.747,
+      "eval_steps_per_second": 2.843,
+      "step": 410
+    },
+    {
+      "epoch": 5.6,
+      "grad_norm": 3.4572854042053223,
+      "learning_rate": 3.0222222222222225e-05,
+      "loss": 1.8135,
+      "step": 420
+    },
+    {
+      "epoch": 5.6,
+      "eval_loss": 2.817023992538452,
+      "eval_runtime": 43.9443,
+      "eval_samples_per_second": 22.756,
+      "eval_steps_per_second": 2.845,
+      "step": 420
+    },
+    {
+      "epoch": 5.733333333333333,
+      "grad_norm": 3.286614179611206,
+      "learning_rate": 2.9037037037037042e-05,
+      "loss": 1.8312,
+      "step": 430
+    },
+    {
+      "epoch": 5.733333333333333,
+      "eval_loss": 2.813601493835449,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 430
+    },
+    {
+      "epoch": 5.866666666666667,
+      "grad_norm": 3.152069568634033,
+      "learning_rate": 2.7851851851851856e-05,
+      "loss": 1.7372,
+      "step": 440
+    },
+    {
+      "epoch": 5.866666666666667,
+      "eval_loss": 2.8068931102752686,
+      "eval_runtime": 43.9514,
+      "eval_samples_per_second": 22.752,
+      "eval_steps_per_second": 2.844,
+      "step": 440
+    },
+    {
+      "epoch": 6.0,
+      "grad_norm": 3.1378376483917236,
+      "learning_rate": 2.6666666666666667e-05,
+      "loss": 1.7966,
+      "step": 450
+    },
+    {
+      "epoch": 6.0,
+      "eval_loss": 2.8000402450561523,
+      "eval_runtime": 43.9182,
+      "eval_samples_per_second": 22.77,
+      "eval_steps_per_second": 2.846,
+      "step": 450
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 7.3737323937792e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-460/README.md

@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-460/adapter_config.json

@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "dense_h_to_4h",
+    "query_key_value",
+    "dense",
+    "dense_4h_to_h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-460/trainer_state.json

@@ -0,0 +1,723 @@
+{
+  "best_metric": 2.5317564010620117,
+  "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
+  "epoch": 6.133333333333334,
+  "eval_steps": 10,
+  "global_step": 460,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.4347652792930603,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 2.4954,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 2.556234359741211,
+      "eval_runtime": 43.818,
+      "eval_samples_per_second": 22.822,
+      "eval_steps_per_second": 2.853,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.40230727195739746,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 2.5574,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 2.552377462387085,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3980488181114197,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 2.4669,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 2.549164056777954,
+      "eval_runtime": 43.8389,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.4006142020225525,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 2.5199,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 2.546046495437622,
+      "eval_runtime": 43.8456,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.4202616512775421,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 2.5619,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 2.5431504249572754,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3871513307094574,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 2.5057,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 2.5413730144500732,
+      "eval_runtime": 43.8646,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.36390039324760437,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 2.4606,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 2.5389301776885986,
+      "eval_runtime": 43.8837,
+      "eval_samples_per_second": 22.788,
+      "eval_steps_per_second": 2.848,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.4081075191497803,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 2.4696,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 2.5368435382843018,
+      "eval_runtime": 43.8696,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.5448070764541626,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 2.4258,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 2.538212776184082,
+      "eval_runtime": 43.8585,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.7155500650405884,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 2.4865,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 2.540060043334961,
+      "eval_runtime": 43.8337,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.7326843738555908,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 2.4391,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 2.5385019779205322,
+      "eval_runtime": 43.8789,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.8026068806648254,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 2.4001,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 2.5356342792510986,
+      "eval_runtime": 43.8699,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.8492558598518372,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 2.387,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 2.5329699516296387,
+      "eval_runtime": 43.8654,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 1.1200364828109741,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 2.3817,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 2.5319204330444336,
+      "eval_runtime": 43.847,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.9766451120376587,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 2.4193,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 2.5317564010620117,
+      "eval_runtime": 43.8504,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 1.0703226327896118,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 2.3341,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 2.5564167499542236,
+      "eval_runtime": 43.8299,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.3115178346633911,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 2.2182,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 2.5810468196868896,
+      "eval_runtime": 43.8366,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.4998687505722046,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 2.2379,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 2.580641269683838,
+      "eval_runtime": 43.8362,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.6269217729568481,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 2.2346,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 2.572070360183716,
+      "eval_runtime": 43.8376,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.5595163106918335,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 2.225,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 2.574326276779175,
+      "eval_runtime": 43.8537,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.673547387123108,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 2.2471,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 2.5765159130096436,
+      "eval_runtime": 43.8369,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 1.5295490026474,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 2.204,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 2.5766921043395996,
+      "eval_runtime": 43.8443,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 1.6709380149841309,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 2.1753,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 2.602360248565674,
+      "eval_runtime": 43.8576,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 2.053478240966797,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 2.0405,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 2.6636874675750732,
+      "eval_runtime": 43.8509,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.8616771697998047,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 2.0265,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 2.6536307334899902,
+      "eval_runtime": 43.8433,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 2.1498146057128906,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 2.1386,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 2.658257246017456,
+      "eval_runtime": 43.8516,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.851,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 2.203857660293579,
+      "learning_rate": 4.8e-05,
+      "loss": 2.0367,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 2.658139228820801,
+      "eval_runtime": 43.8709,
+      "eval_samples_per_second": 22.794,
+      "eval_steps_per_second": 2.849,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 2.0805578231811523,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 2.0226,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 2.646563768386841,
+      "eval_runtime": 43.8726,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 2.27193546295166,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 2.1099,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 2.6486735343933105,
+      "eval_runtime": 43.881,
+      "eval_samples_per_second": 22.789,
+      "eval_steps_per_second": 2.849,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 2.0627055168151855,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 2.0996,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 2.644541025161743,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 2.6526894569396973,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.8896,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 2.7607998847961426,
+      "eval_runtime": 43.8953,
+      "eval_samples_per_second": 22.781,
+      "eval_steps_per_second": 2.848,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 2.813822031021118,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.8568,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 2.7357044219970703,
+      "eval_runtime": 43.8795,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 3.134248733520508,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.9636,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 2.742431640625,
+      "eval_runtime": 43.8639,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 2.727226495742798,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.9148,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 2.7314682006835938,
+      "eval_runtime": 43.852,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.85,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 2.768984079360962,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.9134,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 2.7299180030822754,
+      "eval_runtime": 43.8498,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 350
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 3.0203487873077393,
+      "learning_rate": 3.733333333333334e-05,
+      "loss": 1.9445,
+      "step": 360
+    },
+    {
+      "epoch": 4.8,
+      "eval_loss": 2.7333309650421143,
+      "eval_runtime": 43.8634,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 360
+    },
+    {
+      "epoch": 4.933333333333334,
+      "grad_norm": 2.721759080886841,
+      "learning_rate": 3.614814814814815e-05,
+      "loss": 1.9199,
+      "step": 370
+    },
+    {
+      "epoch": 4.933333333333334,
+      "eval_loss": 2.7230074405670166,
+      "eval_runtime": 43.8351,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 370
+    },
+    {
+      "epoch": 5.066666666666666,
+      "grad_norm": 2.812037467956543,
+      "learning_rate": 3.4962962962962965e-05,
+      "loss": 1.9396,
+      "step": 380
+    },
+    {
+      "epoch": 5.066666666666666,
+      "eval_loss": 2.7738075256347656,
+      "eval_runtime": 43.8405,
+      "eval_samples_per_second": 22.81,
+      "eval_steps_per_second": 2.851,
+      "step": 380
+    },
+    {
+      "epoch": 5.2,
+      "grad_norm": 3.347679376602173,
+      "learning_rate": 3.377777777777778e-05,
+      "loss": 1.8374,
+      "step": 390
+    },
+    {
+      "epoch": 5.2,
+      "eval_loss": 2.830467700958252,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 390
+    },
+    {
+      "epoch": 5.333333333333333,
+      "grad_norm": 3.1343460083007812,
+      "learning_rate": 3.259259259259259e-05,
+      "loss": 1.7472,
+      "step": 400
+    },
+    {
+      "epoch": 5.333333333333333,
+      "eval_loss": 2.8105757236480713,
+      "eval_runtime": 43.9522,
+      "eval_samples_per_second": 22.752,
+      "eval_steps_per_second": 2.844,
+      "step": 400
+    },
+    {
+      "epoch": 5.466666666666667,
+      "grad_norm": 3.431727170944214,
+      "learning_rate": 3.140740740740741e-05,
+      "loss": 1.8274,
+      "step": 410
+    },
+    {
+      "epoch": 5.466666666666667,
+      "eval_loss": 2.816023826599121,
+      "eval_runtime": 43.9615,
+      "eval_samples_per_second": 22.747,
+      "eval_steps_per_second": 2.843,
+      "step": 410
+    },
+    {
+      "epoch": 5.6,
+      "grad_norm": 3.4572854042053223,
+      "learning_rate": 3.0222222222222225e-05,
+      "loss": 1.8135,
+      "step": 420
+    },
+    {
+      "epoch": 5.6,
+      "eval_loss": 2.817023992538452,
+      "eval_runtime": 43.9443,
+      "eval_samples_per_second": 22.756,
+      "eval_steps_per_second": 2.845,
+      "step": 420
+    },
+    {
+      "epoch": 5.733333333333333,
+      "grad_norm": 3.286614179611206,
+      "learning_rate": 2.9037037037037042e-05,
+      "loss": 1.8312,
+      "step": 430
+    },
+    {
+      "epoch": 5.733333333333333,
+      "eval_loss": 2.813601493835449,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 430
+    },
+    {
+      "epoch": 5.866666666666667,
+      "grad_norm": 3.152069568634033,
+      "learning_rate": 2.7851851851851856e-05,
+      "loss": 1.7372,
+      "step": 440
+    },
+    {
+      "epoch": 5.866666666666667,
+      "eval_loss": 2.8068931102752686,
+      "eval_runtime": 43.9514,
+      "eval_samples_per_second": 22.752,
+      "eval_steps_per_second": 2.844,
+      "step": 440
+    },
+    {
+      "epoch": 6.0,
+      "grad_norm": 3.1378376483917236,
+      "learning_rate": 2.6666666666666667e-05,
+      "loss": 1.7966,
+      "step": 450
+    },
+    {
+      "epoch": 6.0,
+      "eval_loss": 2.8000402450561523,
+      "eval_runtime": 43.9182,
+      "eval_samples_per_second": 22.77,
+      "eval_steps_per_second": 2.846,
+      "step": 450
+    },
+    {
+      "epoch": 6.133333333333334,
+      "grad_norm": 3.289393424987793,
+      "learning_rate": 2.5481481481481484e-05,
+      "loss": 1.7021,
+      "step": 460
+    },
+    {
+      "epoch": 6.133333333333334,
+      "eval_loss": 2.8974051475524902,
+      "eval_runtime": 43.8673,
+      "eval_samples_per_second": 22.796,
+      "eval_steps_per_second": 2.85,
+      "step": 460
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 7.53759311364096e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-470/README.md

@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-470/adapter_config.json

@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "dense_h_to_4h",
+    "query_key_value",
+    "dense",
+    "dense_4h_to_h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-470/trainer_state.json

@@ -0,0 +1,738 @@
+{
+  "best_metric": 2.5317564010620117,
+  "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
+  "epoch": 6.266666666666667,
+  "eval_steps": 10,
+  "global_step": 470,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.4347652792930603,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 2.4954,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 2.556234359741211,
+      "eval_runtime": 43.818,
+      "eval_samples_per_second": 22.822,
+      "eval_steps_per_second": 2.853,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.40230727195739746,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 2.5574,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 2.552377462387085,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3980488181114197,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 2.4669,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 2.549164056777954,
+      "eval_runtime": 43.8389,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.4006142020225525,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 2.5199,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 2.546046495437622,
+      "eval_runtime": 43.8456,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.4202616512775421,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 2.5619,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 2.5431504249572754,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3871513307094574,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 2.5057,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 2.5413730144500732,
+      "eval_runtime": 43.8646,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.36390039324760437,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 2.4606,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 2.5389301776885986,
+      "eval_runtime": 43.8837,
+      "eval_samples_per_second": 22.788,
+      "eval_steps_per_second": 2.848,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.4081075191497803,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 2.4696,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 2.5368435382843018,
+      "eval_runtime": 43.8696,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.5448070764541626,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 2.4258,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 2.538212776184082,
+      "eval_runtime": 43.8585,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.7155500650405884,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 2.4865,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 2.540060043334961,
+      "eval_runtime": 43.8337,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.7326843738555908,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 2.4391,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 2.5385019779205322,
+      "eval_runtime": 43.8789,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.8026068806648254,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 2.4001,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 2.5356342792510986,
+      "eval_runtime": 43.8699,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.8492558598518372,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 2.387,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 2.5329699516296387,
+      "eval_runtime": 43.8654,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 1.1200364828109741,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 2.3817,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 2.5319204330444336,
+      "eval_runtime": 43.847,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.9766451120376587,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 2.4193,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 2.5317564010620117,
+      "eval_runtime": 43.8504,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 1.0703226327896118,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 2.3341,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 2.5564167499542236,
+      "eval_runtime": 43.8299,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.3115178346633911,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 2.2182,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 2.5810468196868896,
+      "eval_runtime": 43.8366,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.4998687505722046,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 2.2379,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 2.580641269683838,
+      "eval_runtime": 43.8362,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.6269217729568481,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 2.2346,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 2.572070360183716,
+      "eval_runtime": 43.8376,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.5595163106918335,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 2.225,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 2.574326276779175,
+      "eval_runtime": 43.8537,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.673547387123108,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 2.2471,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 2.5765159130096436,
+      "eval_runtime": 43.8369,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 1.5295490026474,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 2.204,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 2.5766921043395996,
+      "eval_runtime": 43.8443,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 1.6709380149841309,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 2.1753,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 2.602360248565674,
+      "eval_runtime": 43.8576,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 2.053478240966797,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 2.0405,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 2.6636874675750732,
+      "eval_runtime": 43.8509,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.8616771697998047,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 2.0265,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 2.6536307334899902,
+      "eval_runtime": 43.8433,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 2.1498146057128906,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 2.1386,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 2.658257246017456,
+      "eval_runtime": 43.8516,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.851,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 2.203857660293579,
+      "learning_rate": 4.8e-05,
+      "loss": 2.0367,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 2.658139228820801,
+      "eval_runtime": 43.8709,
+      "eval_samples_per_second": 22.794,
+      "eval_steps_per_second": 2.849,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 2.0805578231811523,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 2.0226,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 2.646563768386841,
+      "eval_runtime": 43.8726,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 2.27193546295166,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 2.1099,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 2.6486735343933105,
+      "eval_runtime": 43.881,
+      "eval_samples_per_second": 22.789,
+      "eval_steps_per_second": 2.849,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 2.0627055168151855,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 2.0996,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 2.644541025161743,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 2.6526894569396973,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.8896,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 2.7607998847961426,
+      "eval_runtime": 43.8953,
+      "eval_samples_per_second": 22.781,
+      "eval_steps_per_second": 2.848,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 2.813822031021118,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.8568,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 2.7357044219970703,
+      "eval_runtime": 43.8795,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 3.134248733520508,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.9636,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 2.742431640625,
+      "eval_runtime": 43.8639,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 2.727226495742798,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.9148,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 2.7314682006835938,
+      "eval_runtime": 43.852,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.85,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 2.768984079360962,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.9134,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 2.7299180030822754,
+      "eval_runtime": 43.8498,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 350
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 3.0203487873077393,
+      "learning_rate": 3.733333333333334e-05,
+      "loss": 1.9445,
+      "step": 360
+    },
+    {
+      "epoch": 4.8,
+      "eval_loss": 2.7333309650421143,
+      "eval_runtime": 43.8634,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 360
+    },
+    {
+      "epoch": 4.933333333333334,
+      "grad_norm": 2.721759080886841,
+      "learning_rate": 3.614814814814815e-05,
+      "loss": 1.9199,
+      "step": 370
+    },
+    {
+      "epoch": 4.933333333333334,
+      "eval_loss": 2.7230074405670166,
+      "eval_runtime": 43.8351,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 370
+    },
+    {
+      "epoch": 5.066666666666666,
+      "grad_norm": 2.812037467956543,
+      "learning_rate": 3.4962962962962965e-05,
+      "loss": 1.9396,
+      "step": 380
+    },
+    {
+      "epoch": 5.066666666666666,
+      "eval_loss": 2.7738075256347656,
+      "eval_runtime": 43.8405,
+      "eval_samples_per_second": 22.81,
+      "eval_steps_per_second": 2.851,
+      "step": 380
+    },
+    {
+      "epoch": 5.2,
+      "grad_norm": 3.347679376602173,
+      "learning_rate": 3.377777777777778e-05,
+      "loss": 1.8374,
+      "step": 390
+    },
+    {
+      "epoch": 5.2,
+      "eval_loss": 2.830467700958252,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 390
+    },
+    {
+      "epoch": 5.333333333333333,
+      "grad_norm": 3.1343460083007812,
+      "learning_rate": 3.259259259259259e-05,
+      "loss": 1.7472,
+      "step": 400
+    },
+    {
+      "epoch": 5.333333333333333,
+      "eval_loss": 2.8105757236480713,
+      "eval_runtime": 43.9522,
+      "eval_samples_per_second": 22.752,
+      "eval_steps_per_second": 2.844,
+      "step": 400
+    },
+    {
+      "epoch": 5.466666666666667,
+      "grad_norm": 3.431727170944214,
+      "learning_rate": 3.140740740740741e-05,
+      "loss": 1.8274,
+      "step": 410
+    },
+    {
+      "epoch": 5.466666666666667,
+      "eval_loss": 2.816023826599121,
+      "eval_runtime": 43.9615,
+      "eval_samples_per_second": 22.747,
+      "eval_steps_per_second": 2.843,
+      "step": 410
+    },
+    {
+      "epoch": 5.6,
+      "grad_norm": 3.4572854042053223,
+      "learning_rate": 3.0222222222222225e-05,
+      "loss": 1.8135,
+      "step": 420
+    },
+    {
+      "epoch": 5.6,
+      "eval_loss": 2.817023992538452,
+      "eval_runtime": 43.9443,
+      "eval_samples_per_second": 22.756,
+      "eval_steps_per_second": 2.845,
+      "step": 420
+    },
+    {
+      "epoch": 5.733333333333333,
+      "grad_norm": 3.286614179611206,
+      "learning_rate": 2.9037037037037042e-05,
+      "loss": 1.8312,
+      "step": 430
+    },
+    {
+      "epoch": 5.733333333333333,
+      "eval_loss": 2.813601493835449,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 430
+    },
+    {
+      "epoch": 5.866666666666667,
+      "grad_norm": 3.152069568634033,
+      "learning_rate": 2.7851851851851856e-05,
+      "loss": 1.7372,
+      "step": 440
+    },
+    {
+      "epoch": 5.866666666666667,
+      "eval_loss": 2.8068931102752686,
+      "eval_runtime": 43.9514,
+      "eval_samples_per_second": 22.752,
+      "eval_steps_per_second": 2.844,
+      "step": 440
+    },
+    {
+      "epoch": 6.0,
+      "grad_norm": 3.1378376483917236,
+      "learning_rate": 2.6666666666666667e-05,
+      "loss": 1.7966,
+      "step": 450
+    },
+    {
+      "epoch": 6.0,
+      "eval_loss": 2.8000402450561523,
+      "eval_runtime": 43.9182,
+      "eval_samples_per_second": 22.77,
+      "eval_steps_per_second": 2.846,
+      "step": 450
+    },
+    {
+      "epoch": 6.133333333333334,
+      "grad_norm": 3.289393424987793,
+      "learning_rate": 2.5481481481481484e-05,
+      "loss": 1.7021,
+      "step": 460
+    },
+    {
+      "epoch": 6.133333333333334,
+      "eval_loss": 2.8974051475524902,
+      "eval_runtime": 43.8673,
+      "eval_samples_per_second": 22.796,
+      "eval_steps_per_second": 2.85,
+      "step": 460
+    },
+    {
+      "epoch": 6.266666666666667,
+      "grad_norm": 3.662322998046875,
+      "learning_rate": 2.4296296296296298e-05,
+      "loss": 1.6801,
+      "step": 470
+    },
+    {
+      "epoch": 6.266666666666667,
+      "eval_loss": 2.891542911529541,
+      "eval_runtime": 43.9675,
+      "eval_samples_per_second": 22.744,
+      "eval_steps_per_second": 2.843,
+      "step": 470
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 7.70145383350272e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-480/README.md

@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-480/adapter_config.json

@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "dense_h_to_4h",
+    "query_key_value",
+    "dense",
+    "dense_4h_to_h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-480/trainer_state.json

@@ -0,0 +1,753 @@
+{
+  "best_metric": 2.5317564010620117,
+  "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
+  "epoch": 6.4,
+  "eval_steps": 10,
+  "global_step": 480,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.4347652792930603,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 2.4954,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 2.556234359741211,
+      "eval_runtime": 43.818,
+      "eval_samples_per_second": 22.822,
+      "eval_steps_per_second": 2.853,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.40230727195739746,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 2.5574,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 2.552377462387085,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3980488181114197,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 2.4669,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 2.549164056777954,
+      "eval_runtime": 43.8389,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.4006142020225525,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 2.5199,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 2.546046495437622,
+      "eval_runtime": 43.8456,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.4202616512775421,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 2.5619,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 2.5431504249572754,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3871513307094574,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 2.5057,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 2.5413730144500732,
+      "eval_runtime": 43.8646,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.36390039324760437,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 2.4606,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 2.5389301776885986,
+      "eval_runtime": 43.8837,
+      "eval_samples_per_second": 22.788,
+      "eval_steps_per_second": 2.848,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.4081075191497803,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 2.4696,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 2.5368435382843018,
+      "eval_runtime": 43.8696,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.5448070764541626,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 2.4258,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 2.538212776184082,
+      "eval_runtime": 43.8585,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.7155500650405884,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 2.4865,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 2.540060043334961,
+      "eval_runtime": 43.8337,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.7326843738555908,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 2.4391,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 2.5385019779205322,
+      "eval_runtime": 43.8789,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.8026068806648254,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 2.4001,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 2.5356342792510986,
+      "eval_runtime": 43.8699,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.8492558598518372,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 2.387,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 2.5329699516296387,
+      "eval_runtime": 43.8654,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 1.1200364828109741,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 2.3817,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 2.5319204330444336,
+      "eval_runtime": 43.847,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.9766451120376587,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 2.4193,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 2.5317564010620117,
+      "eval_runtime": 43.8504,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 1.0703226327896118,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 2.3341,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 2.5564167499542236,
+      "eval_runtime": 43.8299,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.3115178346633911,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 2.2182,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 2.5810468196868896,
+      "eval_runtime": 43.8366,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.4998687505722046,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 2.2379,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 2.580641269683838,
+      "eval_runtime": 43.8362,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.6269217729568481,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 2.2346,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 2.572070360183716,
+      "eval_runtime": 43.8376,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.5595163106918335,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 2.225,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 2.574326276779175,
+      "eval_runtime": 43.8537,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.673547387123108,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 2.2471,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 2.5765159130096436,
+      "eval_runtime": 43.8369,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 1.5295490026474,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 2.204,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 2.5766921043395996,
+      "eval_runtime": 43.8443,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 1.6709380149841309,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 2.1753,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 2.602360248565674,
+      "eval_runtime": 43.8576,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 2.053478240966797,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 2.0405,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 2.6636874675750732,
+      "eval_runtime": 43.8509,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.8616771697998047,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 2.0265,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 2.6536307334899902,
+      "eval_runtime": 43.8433,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 2.1498146057128906,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 2.1386,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 2.658257246017456,
+      "eval_runtime": 43.8516,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.851,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 2.203857660293579,
+      "learning_rate": 4.8e-05,
+      "loss": 2.0367,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 2.658139228820801,
+      "eval_runtime": 43.8709,
+      "eval_samples_per_second": 22.794,
+      "eval_steps_per_second": 2.849,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 2.0805578231811523,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 2.0226,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 2.646563768386841,
+      "eval_runtime": 43.8726,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 2.27193546295166,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 2.1099,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 2.6486735343933105,
+      "eval_runtime": 43.881,
+      "eval_samples_per_second": 22.789,
+      "eval_steps_per_second": 2.849,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 2.0627055168151855,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 2.0996,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 2.644541025161743,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 2.6526894569396973,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.8896,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 2.7607998847961426,
+      "eval_runtime": 43.8953,
+      "eval_samples_per_second": 22.781,
+      "eval_steps_per_second": 2.848,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 2.813822031021118,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.8568,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 2.7357044219970703,
+      "eval_runtime": 43.8795,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 3.134248733520508,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.9636,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 2.742431640625,
+      "eval_runtime": 43.8639,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 2.727226495742798,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.9148,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 2.7314682006835938,
+      "eval_runtime": 43.852,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.85,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 2.768984079360962,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.9134,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 2.7299180030822754,
+      "eval_runtime": 43.8498,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 350
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 3.0203487873077393,
+      "learning_rate": 3.733333333333334e-05,
+      "loss": 1.9445,
+      "step": 360
+    },
+    {
+      "epoch": 4.8,
+      "eval_loss": 2.7333309650421143,
+      "eval_runtime": 43.8634,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 360
+    },
+    {
+      "epoch": 4.933333333333334,
+      "grad_norm": 2.721759080886841,
+      "learning_rate": 3.614814814814815e-05,
+      "loss": 1.9199,
+      "step": 370
+    },
+    {
+      "epoch": 4.933333333333334,
+      "eval_loss": 2.7230074405670166,
+      "eval_runtime": 43.8351,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 370
+    },
+    {
+      "epoch": 5.066666666666666,
+      "grad_norm": 2.812037467956543,
+      "learning_rate": 3.4962962962962965e-05,
+      "loss": 1.9396,
+      "step": 380
+    },
+    {
+      "epoch": 5.066666666666666,
+      "eval_loss": 2.7738075256347656,
+      "eval_runtime": 43.8405,
+      "eval_samples_per_second": 22.81,
+      "eval_steps_per_second": 2.851,
+      "step": 380
+    },
+    {
+      "epoch": 5.2,
+      "grad_norm": 3.347679376602173,
+      "learning_rate": 3.377777777777778e-05,
+      "loss": 1.8374,
+      "step": 390
+    },
+    {
+      "epoch": 5.2,
+      "eval_loss": 2.830467700958252,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 390
+    },
+    {
+      "epoch": 5.333333333333333,
+      "grad_norm": 3.1343460083007812,
+      "learning_rate": 3.259259259259259e-05,
+      "loss": 1.7472,
+      "step": 400
+    },
+    {
+      "epoch": 5.333333333333333,
+      "eval_loss": 2.8105757236480713,
+      "eval_runtime": 43.9522,
+      "eval_samples_per_second": 22.752,
+      "eval_steps_per_second": 2.844,
+      "step": 400
+    },
+    {
+      "epoch": 5.466666666666667,
+      "grad_norm": 3.431727170944214,
+      "learning_rate": 3.140740740740741e-05,
+      "loss": 1.8274,
+      "step": 410
+    },
+    {
+      "epoch": 5.466666666666667,
+      "eval_loss": 2.816023826599121,
+      "eval_runtime": 43.9615,
+      "eval_samples_per_second": 22.747,
+      "eval_steps_per_second": 2.843,
+      "step": 410
+    },
+    {
+      "epoch": 5.6,
+      "grad_norm": 3.4572854042053223,
+      "learning_rate": 3.0222222222222225e-05,
+      "loss": 1.8135,
+      "step": 420
+    },
+    {
+      "epoch": 5.6,
+      "eval_loss": 2.817023992538452,
+      "eval_runtime": 43.9443,
+      "eval_samples_per_second": 22.756,
+      "eval_steps_per_second": 2.845,
+      "step": 420
+    },
+    {
+      "epoch": 5.733333333333333,
+      "grad_norm": 3.286614179611206,
+      "learning_rate": 2.9037037037037042e-05,
+      "loss": 1.8312,
+      "step": 430
+    },
+    {
+      "epoch": 5.733333333333333,
+      "eval_loss": 2.813601493835449,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 430
+    },
+    {
+      "epoch": 5.866666666666667,
+      "grad_norm": 3.152069568634033,
+      "learning_rate": 2.7851851851851856e-05,
+      "loss": 1.7372,
+      "step": 440
+    },
+    {
+      "epoch": 5.866666666666667,
+      "eval_loss": 2.8068931102752686,
+      "eval_runtime": 43.9514,
+      "eval_samples_per_second": 22.752,
+      "eval_steps_per_second": 2.844,
+      "step": 440
+    },
+    {
+      "epoch": 6.0,
+      "grad_norm": 3.1378376483917236,
+      "learning_rate": 2.6666666666666667e-05,
+      "loss": 1.7966,
+      "step": 450
+    },
+    {
+      "epoch": 6.0,
+      "eval_loss": 2.8000402450561523,
+      "eval_runtime": 43.9182,
+      "eval_samples_per_second": 22.77,
+      "eval_steps_per_second": 2.846,
+      "step": 450
+    },
+    {
+      "epoch": 6.133333333333334,
+      "grad_norm": 3.289393424987793,
+      "learning_rate": 2.5481481481481484e-05,
+      "loss": 1.7021,
+      "step": 460
+    },
+    {
+      "epoch": 6.133333333333334,
+      "eval_loss": 2.8974051475524902,
+      "eval_runtime": 43.8673,
+      "eval_samples_per_second": 22.796,
+      "eval_steps_per_second": 2.85,
+      "step": 460
+    },
+    {
+      "epoch": 6.266666666666667,
+      "grad_norm": 3.662322998046875,
+      "learning_rate": 2.4296296296296298e-05,
+      "loss": 1.6801,
+      "step": 470
+    },
+    {
+      "epoch": 6.266666666666667,
+      "eval_loss": 2.891542911529541,
+      "eval_runtime": 43.9675,
+      "eval_samples_per_second": 22.744,
+      "eval_steps_per_second": 2.843,
+      "step": 470
+    },
+    {
+      "epoch": 6.4,
+      "grad_norm": 3.6940433979034424,
+      "learning_rate": 2.3111111111111112e-05,
+      "loss": 1.6549,
+      "step": 480
+    },
+    {
+      "epoch": 6.4,
+      "eval_loss": 2.884908676147461,
+      "eval_runtime": 43.9337,
+      "eval_samples_per_second": 22.762,
+      "eval_steps_per_second": 2.845,
+      "step": 480
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 7.86531455336448e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-490/README.md

@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-490/adapter_config.json

@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "dense_h_to_4h",
+    "query_key_value",
+    "dense",
+    "dense_4h_to_h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-490/trainer_state.json

@@ -0,0 +1,768 @@
+{
+  "best_metric": 2.5317564010620117,
+  "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
+  "epoch": 6.533333333333333,
+  "eval_steps": 10,
+  "global_step": 490,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.4347652792930603,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 2.4954,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 2.556234359741211,
+      "eval_runtime": 43.818,
+      "eval_samples_per_second": 22.822,
+      "eval_steps_per_second": 2.853,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.40230727195739746,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 2.5574,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 2.552377462387085,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3980488181114197,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 2.4669,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 2.549164056777954,
+      "eval_runtime": 43.8389,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.4006142020225525,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 2.5199,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 2.546046495437622,
+      "eval_runtime": 43.8456,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.4202616512775421,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 2.5619,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 2.5431504249572754,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3871513307094574,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 2.5057,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 2.5413730144500732,
+      "eval_runtime": 43.8646,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.36390039324760437,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 2.4606,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 2.5389301776885986,
+      "eval_runtime": 43.8837,
+      "eval_samples_per_second": 22.788,
+      "eval_steps_per_second": 2.848,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.4081075191497803,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 2.4696,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 2.5368435382843018,
+      "eval_runtime": 43.8696,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.5448070764541626,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 2.4258,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 2.538212776184082,
+      "eval_runtime": 43.8585,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.7155500650405884,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 2.4865,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 2.540060043334961,
+      "eval_runtime": 43.8337,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.7326843738555908,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 2.4391,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 2.5385019779205322,
+      "eval_runtime": 43.8789,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.8026068806648254,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 2.4001,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 2.5356342792510986,
+      "eval_runtime": 43.8699,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.8492558598518372,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 2.387,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 2.5329699516296387,
+      "eval_runtime": 43.8654,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 1.1200364828109741,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 2.3817,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 2.5319204330444336,
+      "eval_runtime": 43.847,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.9766451120376587,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 2.4193,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 2.5317564010620117,
+      "eval_runtime": 43.8504,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 1.0703226327896118,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 2.3341,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 2.5564167499542236,
+      "eval_runtime": 43.8299,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.3115178346633911,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 2.2182,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 2.5810468196868896,
+      "eval_runtime": 43.8366,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.4998687505722046,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 2.2379,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 2.580641269683838,
+      "eval_runtime": 43.8362,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.6269217729568481,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 2.2346,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 2.572070360183716,
+      "eval_runtime": 43.8376,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.5595163106918335,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 2.225,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 2.574326276779175,
+      "eval_runtime": 43.8537,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.673547387123108,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 2.2471,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 2.5765159130096436,
+      "eval_runtime": 43.8369,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 1.5295490026474,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 2.204,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 2.5766921043395996,
+      "eval_runtime": 43.8443,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 1.6709380149841309,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 2.1753,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 2.602360248565674,
+      "eval_runtime": 43.8576,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 2.053478240966797,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 2.0405,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 2.6636874675750732,
+      "eval_runtime": 43.8509,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.8616771697998047,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 2.0265,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 2.6536307334899902,
+      "eval_runtime": 43.8433,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 2.1498146057128906,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 2.1386,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 2.658257246017456,
+      "eval_runtime": 43.8516,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.851,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 2.203857660293579,
+      "learning_rate": 4.8e-05,
+      "loss": 2.0367,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 2.658139228820801,
+      "eval_runtime": 43.8709,
+      "eval_samples_per_second": 22.794,
+      "eval_steps_per_second": 2.849,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 2.0805578231811523,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 2.0226,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 2.646563768386841,
+      "eval_runtime": 43.8726,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 2.27193546295166,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 2.1099,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 2.6486735343933105,
+      "eval_runtime": 43.881,
+      "eval_samples_per_second": 22.789,
+      "eval_steps_per_second": 2.849,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 2.0627055168151855,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 2.0996,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 2.644541025161743,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 2.6526894569396973,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.8896,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 2.7607998847961426,
+      "eval_runtime": 43.8953,
+      "eval_samples_per_second": 22.781,
+      "eval_steps_per_second": 2.848,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 2.813822031021118,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.8568,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 2.7357044219970703,
+      "eval_runtime": 43.8795,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 3.134248733520508,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.9636,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 2.742431640625,
+      "eval_runtime": 43.8639,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 2.727226495742798,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.9148,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 2.7314682006835938,
+      "eval_runtime": 43.852,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.85,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 2.768984079360962,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.9134,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 2.7299180030822754,
+      "eval_runtime": 43.8498,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 350
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 3.0203487873077393,
+      "learning_rate": 3.733333333333334e-05,
+      "loss": 1.9445,
+      "step": 360
+    },
+    {
+      "epoch": 4.8,
+      "eval_loss": 2.7333309650421143,
+      "eval_runtime": 43.8634,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 360
+    },
+    {
+      "epoch": 4.933333333333334,
+      "grad_norm": 2.721759080886841,
+      "learning_rate": 3.614814814814815e-05,
+      "loss": 1.9199,
+      "step": 370
+    },
+    {
+      "epoch": 4.933333333333334,
+      "eval_loss": 2.7230074405670166,
+      "eval_runtime": 43.8351,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 370
+    },
+    {
+      "epoch": 5.066666666666666,
+      "grad_norm": 2.812037467956543,
+      "learning_rate": 3.4962962962962965e-05,
+      "loss": 1.9396,
+      "step": 380
+    },
+    {
+      "epoch": 5.066666666666666,
+      "eval_loss": 2.7738075256347656,
+      "eval_runtime": 43.8405,
+      "eval_samples_per_second": 22.81,
+      "eval_steps_per_second": 2.851,
+      "step": 380
+    },
+    {
+      "epoch": 5.2,
+      "grad_norm": 3.347679376602173,
+      "learning_rate": 3.377777777777778e-05,
+      "loss": 1.8374,
+      "step": 390
+    },
+    {
+      "epoch": 5.2,
+      "eval_loss": 2.830467700958252,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 390
+    },
+    {
+      "epoch": 5.333333333333333,
+      "grad_norm": 3.1343460083007812,
+      "learning_rate": 3.259259259259259e-05,
+      "loss": 1.7472,
+      "step": 400
+    },
+    {
+      "epoch": 5.333333333333333,
+      "eval_loss": 2.8105757236480713,
+      "eval_runtime": 43.9522,
+      "eval_samples_per_second": 22.752,
+      "eval_steps_per_second": 2.844,
+      "step": 400
+    },
+    {
+      "epoch": 5.466666666666667,
+      "grad_norm": 3.431727170944214,
+      "learning_rate": 3.140740740740741e-05,
+      "loss": 1.8274,
+      "step": 410
+    },
+    {
+      "epoch": 5.466666666666667,
+      "eval_loss": 2.816023826599121,
+      "eval_runtime": 43.9615,
+      "eval_samples_per_second": 22.747,
+      "eval_steps_per_second": 2.843,
+      "step": 410
+    },
+    {
+      "epoch": 5.6,
+      "grad_norm": 3.4572854042053223,
+      "learning_rate": 3.0222222222222225e-05,
+      "loss": 1.8135,
+      "step": 420
+    },
+    {
+      "epoch": 5.6,
+      "eval_loss": 2.817023992538452,
+      "eval_runtime": 43.9443,
+      "eval_samples_per_second": 22.756,
+      "eval_steps_per_second": 2.845,
+      "step": 420
+    },
+    {
+      "epoch": 5.733333333333333,
+      "grad_norm": 3.286614179611206,
+      "learning_rate": 2.9037037037037042e-05,
+      "loss": 1.8312,
+      "step": 430
+    },
+    {
+      "epoch": 5.733333333333333,
+      "eval_loss": 2.813601493835449,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 430
+    },
+    {
+      "epoch": 5.866666666666667,
+      "grad_norm": 3.152069568634033,
+      "learning_rate": 2.7851851851851856e-05,
+      "loss": 1.7372,
+      "step": 440
+    },
+    {
+      "epoch": 5.866666666666667,
+      "eval_loss": 2.8068931102752686,
+      "eval_runtime": 43.9514,
+      "eval_samples_per_second": 22.752,
+      "eval_steps_per_second": 2.844,
+      "step": 440
+    },
+    {
+      "epoch": 6.0,
+      "grad_norm": 3.1378376483917236,
+      "learning_rate": 2.6666666666666667e-05,
+      "loss": 1.7966,
+      "step": 450
+    },
+    {
+      "epoch": 6.0,
+      "eval_loss": 2.8000402450561523,
+      "eval_runtime": 43.9182,
+      "eval_samples_per_second": 22.77,
+      "eval_steps_per_second": 2.846,
+      "step": 450
+    },
+    {
+      "epoch": 6.133333333333334,
+      "grad_norm": 3.289393424987793,
+      "learning_rate": 2.5481481481481484e-05,
+      "loss": 1.7021,
+      "step": 460
+    },
+    {
+      "epoch": 6.133333333333334,
+      "eval_loss": 2.8974051475524902,
+      "eval_runtime": 43.8673,
+      "eval_samples_per_second": 22.796,
+      "eval_steps_per_second": 2.85,
+      "step": 460
+    },
+    {
+      "epoch": 6.266666666666667,
+      "grad_norm": 3.662322998046875,
+      "learning_rate": 2.4296296296296298e-05,
+      "loss": 1.6801,
+      "step": 470
+    },
+    {
+      "epoch": 6.266666666666667,
+      "eval_loss": 2.891542911529541,
+      "eval_runtime": 43.9675,
+      "eval_samples_per_second": 22.744,
+      "eval_steps_per_second": 2.843,
+      "step": 470
+    },
+    {
+      "epoch": 6.4,
+      "grad_norm": 3.6940433979034424,
+      "learning_rate": 2.3111111111111112e-05,
+      "loss": 1.6549,
+      "step": 480
+    },
+    {
+      "epoch": 6.4,
+      "eval_loss": 2.884908676147461,
+      "eval_runtime": 43.9337,
+      "eval_samples_per_second": 22.762,
+      "eval_steps_per_second": 2.845,
+      "step": 480
+    },
+    {
+      "epoch": 6.533333333333333,
+      "grad_norm": 3.8792476654052734,
+      "learning_rate": 2.192592592592593e-05,
+      "loss": 1.6964,
+      "step": 490
+    },
+    {
+      "epoch": 6.533333333333333,
+      "eval_loss": 2.8918919563293457,
+      "eval_runtime": 43.9143,
+      "eval_samples_per_second": 22.772,
+      "eval_steps_per_second": 2.846,
+      "step": 490
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 8.02917527322624e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-500/README.md

@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-500/adapter_config.json

@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "dense_h_to_4h",
+    "query_key_value",
+    "dense",
+    "dense_4h_to_h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-500/trainer_state.json

@@ -0,0 +1,783 @@
+{
+  "best_metric": 2.5317564010620117,
+  "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
+  "epoch": 6.666666666666667,
+  "eval_steps": 10,
+  "global_step": 500,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.4347652792930603,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 2.4954,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 2.556234359741211,
+      "eval_runtime": 43.818,
+      "eval_samples_per_second": 22.822,
+      "eval_steps_per_second": 2.853,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.40230727195739746,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 2.5574,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 2.552377462387085,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3980488181114197,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 2.4669,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 2.549164056777954,
+      "eval_runtime": 43.8389,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.4006142020225525,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 2.5199,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 2.546046495437622,
+      "eval_runtime": 43.8456,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.4202616512775421,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 2.5619,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 2.5431504249572754,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3871513307094574,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 2.5057,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 2.5413730144500732,
+      "eval_runtime": 43.8646,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.36390039324760437,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 2.4606,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 2.5389301776885986,
+      "eval_runtime": 43.8837,
+      "eval_samples_per_second": 22.788,
+      "eval_steps_per_second": 2.848,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.4081075191497803,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 2.4696,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 2.5368435382843018,
+      "eval_runtime": 43.8696,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.5448070764541626,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 2.4258,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 2.538212776184082,
+      "eval_runtime": 43.8585,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.7155500650405884,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 2.4865,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 2.540060043334961,
+      "eval_runtime": 43.8337,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.7326843738555908,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 2.4391,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 2.5385019779205322,
+      "eval_runtime": 43.8789,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.8026068806648254,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 2.4001,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 2.5356342792510986,
+      "eval_runtime": 43.8699,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.8492558598518372,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 2.387,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 2.5329699516296387,
+      "eval_runtime": 43.8654,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 1.1200364828109741,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 2.3817,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 2.5319204330444336,
+      "eval_runtime": 43.847,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.9766451120376587,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 2.4193,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 2.5317564010620117,
+      "eval_runtime": 43.8504,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 1.0703226327896118,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 2.3341,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 2.5564167499542236,
+      "eval_runtime": 43.8299,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.3115178346633911,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 2.2182,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 2.5810468196868896,
+      "eval_runtime": 43.8366,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.4998687505722046,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 2.2379,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 2.580641269683838,
+      "eval_runtime": 43.8362,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.6269217729568481,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 2.2346,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 2.572070360183716,
+      "eval_runtime": 43.8376,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.5595163106918335,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 2.225,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 2.574326276779175,
+      "eval_runtime": 43.8537,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.673547387123108,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 2.2471,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 2.5765159130096436,
+      "eval_runtime": 43.8369,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 1.5295490026474,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 2.204,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 2.5766921043395996,
+      "eval_runtime": 43.8443,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 1.6709380149841309,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 2.1753,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 2.602360248565674,
+      "eval_runtime": 43.8576,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 2.053478240966797,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 2.0405,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 2.6636874675750732,
+      "eval_runtime": 43.8509,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.8616771697998047,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 2.0265,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 2.6536307334899902,
+      "eval_runtime": 43.8433,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 2.1498146057128906,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 2.1386,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 2.658257246017456,
+      "eval_runtime": 43.8516,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.851,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 2.203857660293579,
+      "learning_rate": 4.8e-05,
+      "loss": 2.0367,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 2.658139228820801,
+      "eval_runtime": 43.8709,
+      "eval_samples_per_second": 22.794,
+      "eval_steps_per_second": 2.849,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 2.0805578231811523,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 2.0226,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 2.646563768386841,
+      "eval_runtime": 43.8726,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 2.27193546295166,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 2.1099,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 2.6486735343933105,
+      "eval_runtime": 43.881,
+      "eval_samples_per_second": 22.789,
+      "eval_steps_per_second": 2.849,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 2.0627055168151855,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 2.0996,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 2.644541025161743,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 2.6526894569396973,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.8896,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 2.7607998847961426,
+      "eval_runtime": 43.8953,
+      "eval_samples_per_second": 22.781,
+      "eval_steps_per_second": 2.848,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 2.813822031021118,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.8568,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 2.7357044219970703,
+      "eval_runtime": 43.8795,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 3.134248733520508,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.9636,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 2.742431640625,
+      "eval_runtime": 43.8639,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 2.727226495742798,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.9148,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 2.7314682006835938,
+      "eval_runtime": 43.852,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.85,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 2.768984079360962,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.9134,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 2.7299180030822754,
+      "eval_runtime": 43.8498,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 350
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 3.0203487873077393,
+      "learning_rate": 3.733333333333334e-05,
+      "loss": 1.9445,
+      "step": 360
+    },
+    {
+      "epoch": 4.8,
+      "eval_loss": 2.7333309650421143,
+      "eval_runtime": 43.8634,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 360
+    },
+    {
+      "epoch": 4.933333333333334,
+      "grad_norm": 2.721759080886841,
+      "learning_rate": 3.614814814814815e-05,
+      "loss": 1.9199,
+      "step": 370
+    },
+    {
+      "epoch": 4.933333333333334,
+      "eval_loss": 2.7230074405670166,
+      "eval_runtime": 43.8351,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 370
+    },
+    {
+      "epoch": 5.066666666666666,
+      "grad_norm": 2.812037467956543,
+      "learning_rate": 3.4962962962962965e-05,
+      "loss": 1.9396,
+      "step": 380
+    },
+    {
+      "epoch": 5.066666666666666,
+      "eval_loss": 2.7738075256347656,
+      "eval_runtime": 43.8405,
+      "eval_samples_per_second": 22.81,
+      "eval_steps_per_second": 2.851,
+      "step": 380
+    },
+    {
+      "epoch": 5.2,
+      "grad_norm": 3.347679376602173,
+      "learning_rate": 3.377777777777778e-05,
+      "loss": 1.8374,
+      "step": 390
+    },
+    {
+      "epoch": 5.2,
+      "eval_loss": 2.830467700958252,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 390
+    },
+    {
+      "epoch": 5.333333333333333,
+      "grad_norm": 3.1343460083007812,
+      "learning_rate": 3.259259259259259e-05,
+      "loss": 1.7472,
+      "step": 400
+    },
+    {
+      "epoch": 5.333333333333333,
+      "eval_loss": 2.8105757236480713,
+      "eval_runtime": 43.9522,
+      "eval_samples_per_second": 22.752,
+      "eval_steps_per_second": 2.844,
+      "step": 400
+    },
+    {
+      "epoch": 5.466666666666667,
+      "grad_norm": 3.431727170944214,
+      "learning_rate": 3.140740740740741e-05,
+      "loss": 1.8274,
+      "step": 410
+    },
+    {
+      "epoch": 5.466666666666667,
+      "eval_loss": 2.816023826599121,
+      "eval_runtime": 43.9615,
+      "eval_samples_per_second": 22.747,
+      "eval_steps_per_second": 2.843,
+      "step": 410
+    },
+    {
+      "epoch": 5.6,
+      "grad_norm": 3.4572854042053223,
+      "learning_rate": 3.0222222222222225e-05,
+      "loss": 1.8135,
+      "step": 420
+    },
+    {
+      "epoch": 5.6,
+      "eval_loss": 2.817023992538452,
+      "eval_runtime": 43.9443,
+      "eval_samples_per_second": 22.756,
+      "eval_steps_per_second": 2.845,
+      "step": 420
+    },
+    {
+      "epoch": 5.733333333333333,
+      "grad_norm": 3.286614179611206,
+      "learning_rate": 2.9037037037037042e-05,
+      "loss": 1.8312,
+      "step": 430
+    },
+    {
+      "epoch": 5.733333333333333,
+      "eval_loss": 2.813601493835449,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 430
+    },
+    {
+      "epoch": 5.866666666666667,
+      "grad_norm": 3.152069568634033,
+      "learning_rate": 2.7851851851851856e-05,
+      "loss": 1.7372,
+      "step": 440
+    },
+    {
+      "epoch": 5.866666666666667,
+      "eval_loss": 2.8068931102752686,
+      "eval_runtime": 43.9514,
+      "eval_samples_per_second": 22.752,
+      "eval_steps_per_second": 2.844,
+      "step": 440
+    },
+    {
+      "epoch": 6.0,
+      "grad_norm": 3.1378376483917236,
+      "learning_rate": 2.6666666666666667e-05,
+      "loss": 1.7966,
+      "step": 450
+    },
+    {
+      "epoch": 6.0,
+      "eval_loss": 2.8000402450561523,
+      "eval_runtime": 43.9182,
+      "eval_samples_per_second": 22.77,
+      "eval_steps_per_second": 2.846,
+      "step": 450
+    },
+    {
+      "epoch": 6.133333333333334,
+      "grad_norm": 3.289393424987793,
+      "learning_rate": 2.5481481481481484e-05,
+      "loss": 1.7021,
+      "step": 460
+    },
+    {
+      "epoch": 6.133333333333334,
+      "eval_loss": 2.8974051475524902,
+      "eval_runtime": 43.8673,
+      "eval_samples_per_second": 22.796,
+      "eval_steps_per_second": 2.85,
+      "step": 460
+    },
+    {
+      "epoch": 6.266666666666667,
+      "grad_norm": 3.662322998046875,
+      "learning_rate": 2.4296296296296298e-05,
+      "loss": 1.6801,
+      "step": 470
+    },
+    {
+      "epoch": 6.266666666666667,
+      "eval_loss": 2.891542911529541,
+      "eval_runtime": 43.9675,
+      "eval_samples_per_second": 22.744,
+      "eval_steps_per_second": 2.843,
+      "step": 470
+    },
+    {
+      "epoch": 6.4,
+      "grad_norm": 3.6940433979034424,
+      "learning_rate": 2.3111111111111112e-05,
+      "loss": 1.6549,
+      "step": 480
+    },
+    {
+      "epoch": 6.4,
+      "eval_loss": 2.884908676147461,
+      "eval_runtime": 43.9337,
+      "eval_samples_per_second": 22.762,
+      "eval_steps_per_second": 2.845,
+      "step": 480
+    },
+    {
+      "epoch": 6.533333333333333,
+      "grad_norm": 3.8792476654052734,
+      "learning_rate": 2.192592592592593e-05,
+      "loss": 1.6964,
+      "step": 490
+    },
+    {
+      "epoch": 6.533333333333333,
+      "eval_loss": 2.8918919563293457,
+      "eval_runtime": 43.9143,
+      "eval_samples_per_second": 22.772,
+      "eval_steps_per_second": 2.846,
+      "step": 490
+    },
+    {
+      "epoch": 6.666666666666667,
+      "grad_norm": 3.8439388275146484,
+      "learning_rate": 2.074074074074074e-05,
+      "loss": 1.7524,
+      "step": 500
+    },
+    {
+      "epoch": 6.666666666666667,
+      "eval_loss": 2.890720844268799,
+      "eval_runtime": 43.9225,
+      "eval_samples_per_second": 22.767,
+      "eval_steps_per_second": 2.846,
+      "step": 500
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 8.193035993088e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-510/README.md

@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-510/adapter_config.json

@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "dense_h_to_4h",
+    "query_key_value",
+    "dense",
+    "dense_4h_to_h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-510/trainer_state.json

@@ -0,0 +1,798 @@
+{
+  "best_metric": 2.5317564010620117,
+  "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
+  "epoch": 6.8,
+  "eval_steps": 10,
+  "global_step": 510,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.4347652792930603,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 2.4954,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 2.556234359741211,
+      "eval_runtime": 43.818,
+      "eval_samples_per_second": 22.822,
+      "eval_steps_per_second": 2.853,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.40230727195739746,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 2.5574,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 2.552377462387085,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3980488181114197,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 2.4669,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 2.549164056777954,
+      "eval_runtime": 43.8389,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.4006142020225525,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 2.5199,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 2.546046495437622,
+      "eval_runtime": 43.8456,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.4202616512775421,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 2.5619,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 2.5431504249572754,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3871513307094574,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 2.5057,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 2.5413730144500732,
+      "eval_runtime": 43.8646,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.36390039324760437,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 2.4606,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 2.5389301776885986,
+      "eval_runtime": 43.8837,
+      "eval_samples_per_second": 22.788,
+      "eval_steps_per_second": 2.848,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.4081075191497803,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 2.4696,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 2.5368435382843018,
+      "eval_runtime": 43.8696,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.5448070764541626,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 2.4258,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 2.538212776184082,
+      "eval_runtime": 43.8585,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.7155500650405884,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 2.4865,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 2.540060043334961,
+      "eval_runtime": 43.8337,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.7326843738555908,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 2.4391,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 2.5385019779205322,
+      "eval_runtime": 43.8789,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.8026068806648254,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 2.4001,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 2.5356342792510986,
+      "eval_runtime": 43.8699,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.8492558598518372,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 2.387,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 2.5329699516296387,
+      "eval_runtime": 43.8654,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 1.1200364828109741,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 2.3817,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 2.5319204330444336,
+      "eval_runtime": 43.847,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.9766451120376587,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 2.4193,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 2.5317564010620117,
+      "eval_runtime": 43.8504,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 1.0703226327896118,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 2.3341,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 2.5564167499542236,
+      "eval_runtime": 43.8299,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.3115178346633911,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 2.2182,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 2.5810468196868896,
+      "eval_runtime": 43.8366,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.4998687505722046,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 2.2379,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 2.580641269683838,
+      "eval_runtime": 43.8362,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.6269217729568481,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 2.2346,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 2.572070360183716,
+      "eval_runtime": 43.8376,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.5595163106918335,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 2.225,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 2.574326276779175,
+      "eval_runtime": 43.8537,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.673547387123108,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 2.2471,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 2.5765159130096436,
+      "eval_runtime": 43.8369,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 1.5295490026474,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 2.204,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 2.5766921043395996,
+      "eval_runtime": 43.8443,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 1.6709380149841309,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 2.1753,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 2.602360248565674,
+      "eval_runtime": 43.8576,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 2.053478240966797,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 2.0405,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 2.6636874675750732,
+      "eval_runtime": 43.8509,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.8616771697998047,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 2.0265,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 2.6536307334899902,
+      "eval_runtime": 43.8433,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 2.1498146057128906,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 2.1386,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 2.658257246017456,
+      "eval_runtime": 43.8516,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.851,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 2.203857660293579,
+      "learning_rate": 4.8e-05,
+      "loss": 2.0367,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 2.658139228820801,
+      "eval_runtime": 43.8709,
+      "eval_samples_per_second": 22.794,
+      "eval_steps_per_second": 2.849,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 2.0805578231811523,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 2.0226,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 2.646563768386841,
+      "eval_runtime": 43.8726,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 2.27193546295166,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 2.1099,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 2.6486735343933105,
+      "eval_runtime": 43.881,
+      "eval_samples_per_second": 22.789,
+      "eval_steps_per_second": 2.849,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 2.0627055168151855,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 2.0996,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 2.644541025161743,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 2.6526894569396973,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.8896,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 2.7607998847961426,
+      "eval_runtime": 43.8953,
+      "eval_samples_per_second": 22.781,
+      "eval_steps_per_second": 2.848,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 2.813822031021118,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.8568,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 2.7357044219970703,
+      "eval_runtime": 43.8795,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 3.134248733520508,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.9636,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 2.742431640625,
+      "eval_runtime": 43.8639,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 2.727226495742798,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.9148,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 2.7314682006835938,
+      "eval_runtime": 43.852,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.85,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 2.768984079360962,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.9134,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 2.7299180030822754,
+      "eval_runtime": 43.8498,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 350
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 3.0203487873077393,
+      "learning_rate": 3.733333333333334e-05,
+      "loss": 1.9445,
+      "step": 360
+    },
+    {
+      "epoch": 4.8,
+      "eval_loss": 2.7333309650421143,
+      "eval_runtime": 43.8634,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 360
+    },
+    {
+      "epoch": 4.933333333333334,
+      "grad_norm": 2.721759080886841,
+      "learning_rate": 3.614814814814815e-05,
+      "loss": 1.9199,
+      "step": 370
+    },
+    {
+      "epoch": 4.933333333333334,
+      "eval_loss": 2.7230074405670166,
+      "eval_runtime": 43.8351,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 370
+    },
+    {
+      "epoch": 5.066666666666666,
+      "grad_norm": 2.812037467956543,
+      "learning_rate": 3.4962962962962965e-05,
+      "loss": 1.9396,
+      "step": 380
+    },
+    {
+      "epoch": 5.066666666666666,
+      "eval_loss": 2.7738075256347656,
+      "eval_runtime": 43.8405,
+      "eval_samples_per_second": 22.81,
+      "eval_steps_per_second": 2.851,
+      "step": 380
+    },
+    {
+      "epoch": 5.2,
+      "grad_norm": 3.347679376602173,
+      "learning_rate": 3.377777777777778e-05,
+      "loss": 1.8374,
+      "step": 390
+    },
+    {
+      "epoch": 5.2,
+      "eval_loss": 2.830467700958252,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 390
+    },
+    {
+      "epoch": 5.333333333333333,
+      "grad_norm": 3.1343460083007812,
+      "learning_rate": 3.259259259259259e-05,
+      "loss": 1.7472,
+      "step": 400
+    },
+    {
+      "epoch": 5.333333333333333,
+      "eval_loss": 2.8105757236480713,
+      "eval_runtime": 43.9522,
+      "eval_samples_per_second": 22.752,
+      "eval_steps_per_second": 2.844,
+      "step": 400
+    },
+    {
+      "epoch": 5.466666666666667,
+      "grad_norm": 3.431727170944214,
+      "learning_rate": 3.140740740740741e-05,
+      "loss": 1.8274,
+      "step": 410
+    },
+    {
+      "epoch": 5.466666666666667,
+      "eval_loss": 2.816023826599121,
+      "eval_runtime": 43.9615,
+      "eval_samples_per_second": 22.747,
+      "eval_steps_per_second": 2.843,
+      "step": 410
+    },
+    {
+      "epoch": 5.6,
+      "grad_norm": 3.4572854042053223,
+      "learning_rate": 3.0222222222222225e-05,
+      "loss": 1.8135,
+      "step": 420
+    },
+    {
+      "epoch": 5.6,
+      "eval_loss": 2.817023992538452,
+      "eval_runtime": 43.9443,
+      "eval_samples_per_second": 22.756,
+      "eval_steps_per_second": 2.845,
+      "step": 420
+    },
+    {
+      "epoch": 5.733333333333333,
+      "grad_norm": 3.286614179611206,
+      "learning_rate": 2.9037037037037042e-05,
+      "loss": 1.8312,
+      "step": 430
+    },
+    {
+      "epoch": 5.733333333333333,
+      "eval_loss": 2.813601493835449,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 430
+    },
+    {
+      "epoch": 5.866666666666667,
+      "grad_norm": 3.152069568634033,
+      "learning_rate": 2.7851851851851856e-05,
+      "loss": 1.7372,
+      "step": 440
+    },
+    {
+      "epoch": 5.866666666666667,
+      "eval_loss": 2.8068931102752686,
+      "eval_runtime": 43.9514,
+      "eval_samples_per_second": 22.752,
+      "eval_steps_per_second": 2.844,
+      "step": 440
+    },
+    {
+      "epoch": 6.0,
+      "grad_norm": 3.1378376483917236,
+      "learning_rate": 2.6666666666666667e-05,
+      "loss": 1.7966,
+      "step": 450
+    },
+    {
+      "epoch": 6.0,
+      "eval_loss": 2.8000402450561523,
+      "eval_runtime": 43.9182,
+      "eval_samples_per_second": 22.77,
+      "eval_steps_per_second": 2.846,
+      "step": 450
+    },
+    {
+      "epoch": 6.133333333333334,
+      "grad_norm": 3.289393424987793,
+      "learning_rate": 2.5481481481481484e-05,
+      "loss": 1.7021,
+      "step": 460
+    },
+    {
+      "epoch": 6.133333333333334,
+      "eval_loss": 2.8974051475524902,
+      "eval_runtime": 43.8673,
+      "eval_samples_per_second": 22.796,
+      "eval_steps_per_second": 2.85,
+      "step": 460
+    },
+    {
+      "epoch": 6.266666666666667,
+      "grad_norm": 3.662322998046875,
+      "learning_rate": 2.4296296296296298e-05,
+      "loss": 1.6801,
+      "step": 470
+    },
+    {
+      "epoch": 6.266666666666667,
+      "eval_loss": 2.891542911529541,
+      "eval_runtime": 43.9675,
+      "eval_samples_per_second": 22.744,
+      "eval_steps_per_second": 2.843,
+      "step": 470
+    },
+    {
+      "epoch": 6.4,
+      "grad_norm": 3.6940433979034424,
+      "learning_rate": 2.3111111111111112e-05,
+      "loss": 1.6549,
+      "step": 480
+    },
+    {
+      "epoch": 6.4,
+      "eval_loss": 2.884908676147461,
+      "eval_runtime": 43.9337,
+      "eval_samples_per_second": 22.762,
+      "eval_steps_per_second": 2.845,
+      "step": 480
+    },
+    {
+      "epoch": 6.533333333333333,
+      "grad_norm": 3.8792476654052734,
+      "learning_rate": 2.192592592592593e-05,
+      "loss": 1.6964,
+      "step": 490
+    },
+    {
+      "epoch": 6.533333333333333,
+      "eval_loss": 2.8918919563293457,
+      "eval_runtime": 43.9143,
+      "eval_samples_per_second": 22.772,
+      "eval_steps_per_second": 2.846,
+      "step": 490
+    },
+    {
+      "epoch": 6.666666666666667,
+      "grad_norm": 3.8439388275146484,
+      "learning_rate": 2.074074074074074e-05,
+      "loss": 1.7524,
+      "step": 500
+    },
+    {
+      "epoch": 6.666666666666667,
+      "eval_loss": 2.890720844268799,
+      "eval_runtime": 43.9225,
+      "eval_samples_per_second": 22.767,
+      "eval_steps_per_second": 2.846,
+      "step": 500
+    },
+    {
+      "epoch": 6.8,
+      "grad_norm": 3.7934892177581787,
+      "learning_rate": 1.9555555555555557e-05,
+      "loss": 1.7211,
+      "step": 510
+    },
+    {
+      "epoch": 6.8,
+      "eval_loss": 2.8894593715667725,
+      "eval_runtime": 43.9778,
+      "eval_samples_per_second": 22.739,
+      "eval_steps_per_second": 2.842,
+      "step": 510
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 8.35689671294976e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-520/README.md

@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-520/adapter_config.json

@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "dense_h_to_4h",
+    "query_key_value",
+    "dense",
+    "dense_4h_to_h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-520/trainer_state.json

@@ -0,0 +1,813 @@
+{
+  "best_metric": 2.5317564010620117,
+  "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
+  "epoch": 6.933333333333334,
+  "eval_steps": 10,
+  "global_step": 520,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.4347652792930603,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 2.4954,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 2.556234359741211,
+      "eval_runtime": 43.818,
+      "eval_samples_per_second": 22.822,
+      "eval_steps_per_second": 2.853,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.40230727195739746,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 2.5574,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 2.552377462387085,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3980488181114197,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 2.4669,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 2.549164056777954,
+      "eval_runtime": 43.8389,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.4006142020225525,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 2.5199,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 2.546046495437622,
+      "eval_runtime": 43.8456,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.4202616512775421,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 2.5619,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 2.5431504249572754,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3871513307094574,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 2.5057,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 2.5413730144500732,
+      "eval_runtime": 43.8646,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.36390039324760437,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 2.4606,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 2.5389301776885986,
+      "eval_runtime": 43.8837,
+      "eval_samples_per_second": 22.788,
+      "eval_steps_per_second": 2.848,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.4081075191497803,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 2.4696,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 2.5368435382843018,
+      "eval_runtime": 43.8696,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.5448070764541626,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 2.4258,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 2.538212776184082,
+      "eval_runtime": 43.8585,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.7155500650405884,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 2.4865,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 2.540060043334961,
+      "eval_runtime": 43.8337,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.7326843738555908,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 2.4391,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 2.5385019779205322,
+      "eval_runtime": 43.8789,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.8026068806648254,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 2.4001,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 2.5356342792510986,
+      "eval_runtime": 43.8699,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.8492558598518372,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 2.387,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 2.5329699516296387,
+      "eval_runtime": 43.8654,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 1.1200364828109741,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 2.3817,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 2.5319204330444336,
+      "eval_runtime": 43.847,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.9766451120376587,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 2.4193,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 2.5317564010620117,
+      "eval_runtime": 43.8504,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 1.0703226327896118,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 2.3341,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 2.5564167499542236,
+      "eval_runtime": 43.8299,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.3115178346633911,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 2.2182,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 2.5810468196868896,
+      "eval_runtime": 43.8366,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.4998687505722046,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 2.2379,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 2.580641269683838,
+      "eval_runtime": 43.8362,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.6269217729568481,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 2.2346,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 2.572070360183716,
+      "eval_runtime": 43.8376,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.5595163106918335,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 2.225,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 2.574326276779175,
+      "eval_runtime": 43.8537,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.673547387123108,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 2.2471,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 2.5765159130096436,
+      "eval_runtime": 43.8369,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 1.5295490026474,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 2.204,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 2.5766921043395996,
+      "eval_runtime": 43.8443,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 1.6709380149841309,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 2.1753,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 2.602360248565674,
+      "eval_runtime": 43.8576,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 2.053478240966797,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 2.0405,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 2.6636874675750732,
+      "eval_runtime": 43.8509,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.8616771697998047,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 2.0265,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 2.6536307334899902,
+      "eval_runtime": 43.8433,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 2.1498146057128906,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 2.1386,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 2.658257246017456,
+      "eval_runtime": 43.8516,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.851,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 2.203857660293579,
+      "learning_rate": 4.8e-05,
+      "loss": 2.0367,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 2.658139228820801,
+      "eval_runtime": 43.8709,
+      "eval_samples_per_second": 22.794,
+      "eval_steps_per_second": 2.849,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 2.0805578231811523,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 2.0226,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 2.646563768386841,
+      "eval_runtime": 43.8726,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 2.27193546295166,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 2.1099,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 2.6486735343933105,
+      "eval_runtime": 43.881,
+      "eval_samples_per_second": 22.789,
+      "eval_steps_per_second": 2.849,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 2.0627055168151855,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 2.0996,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 2.644541025161743,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 2.6526894569396973,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.8896,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 2.7607998847961426,
+      "eval_runtime": 43.8953,
+      "eval_samples_per_second": 22.781,
+      "eval_steps_per_second": 2.848,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 2.813822031021118,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.8568,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 2.7357044219970703,
+      "eval_runtime": 43.8795,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 3.134248733520508,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.9636,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 2.742431640625,
+      "eval_runtime": 43.8639,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 2.727226495742798,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.9148,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 2.7314682006835938,
+      "eval_runtime": 43.852,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.85,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 2.768984079360962,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.9134,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 2.7299180030822754,
+      "eval_runtime": 43.8498,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 350
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 3.0203487873077393,
+      "learning_rate": 3.733333333333334e-05,
+      "loss": 1.9445,
+      "step": 360
+    },
+    {
+      "epoch": 4.8,
+      "eval_loss": 2.7333309650421143,
+      "eval_runtime": 43.8634,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 360
+    },
+    {
+      "epoch": 4.933333333333334,
+      "grad_norm": 2.721759080886841,
+      "learning_rate": 3.614814814814815e-05,
+      "loss": 1.9199,
+      "step": 370
+    },
+    {
+      "epoch": 4.933333333333334,
+      "eval_loss": 2.7230074405670166,
+      "eval_runtime": 43.8351,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 370
+    },
+    {
+      "epoch": 5.066666666666666,
+      "grad_norm": 2.812037467956543,
+      "learning_rate": 3.4962962962962965e-05,
+      "loss": 1.9396,
+      "step": 380
+    },
+    {
+      "epoch": 5.066666666666666,
+      "eval_loss": 2.7738075256347656,
+      "eval_runtime": 43.8405,
+      "eval_samples_per_second": 22.81,
+      "eval_steps_per_second": 2.851,
+      "step": 380
+    },
+    {
+      "epoch": 5.2,
+      "grad_norm": 3.347679376602173,
+      "learning_rate": 3.377777777777778e-05,
+      "loss": 1.8374,
+      "step": 390
+    },
+    {
+      "epoch": 5.2,
+      "eval_loss": 2.830467700958252,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 390
+    },
+    {
+      "epoch": 5.333333333333333,
+      "grad_norm": 3.1343460083007812,
+      "learning_rate": 3.259259259259259e-05,
+      "loss": 1.7472,
+      "step": 400
+    },
+    {
+      "epoch": 5.333333333333333,
+      "eval_loss": 2.8105757236480713,
+      "eval_runtime": 43.9522,
+      "eval_samples_per_second": 22.752,
+      "eval_steps_per_second": 2.844,
+      "step": 400
+    },
+    {
+      "epoch": 5.466666666666667,
+      "grad_norm": 3.431727170944214,
+      "learning_rate": 3.140740740740741e-05,
+      "loss": 1.8274,
+      "step": 410
+    },
+    {
+      "epoch": 5.466666666666667,
+      "eval_loss": 2.816023826599121,
+      "eval_runtime": 43.9615,
+      "eval_samples_per_second": 22.747,
+      "eval_steps_per_second": 2.843,
+      "step": 410
+    },
+    {
+      "epoch": 5.6,
+      "grad_norm": 3.4572854042053223,
+      "learning_rate": 3.0222222222222225e-05,
+      "loss": 1.8135,
+      "step": 420
+    },
+    {
+      "epoch": 5.6,
+      "eval_loss": 2.817023992538452,
+      "eval_runtime": 43.9443,
+      "eval_samples_per_second": 22.756,
+      "eval_steps_per_second": 2.845,
+      "step": 420
+    },
+    {
+      "epoch": 5.733333333333333,
+      "grad_norm": 3.286614179611206,
+      "learning_rate": 2.9037037037037042e-05,
+      "loss": 1.8312,
+      "step": 430
+    },
+    {
+      "epoch": 5.733333333333333,
+      "eval_loss": 2.813601493835449,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 430
+    },
+    {
+      "epoch": 5.866666666666667,
+      "grad_norm": 3.152069568634033,
+      "learning_rate": 2.7851851851851856e-05,
+      "loss": 1.7372,
+      "step": 440
+    },
+    {
+      "epoch": 5.866666666666667,
+      "eval_loss": 2.8068931102752686,
+      "eval_runtime": 43.9514,
+      "eval_samples_per_second": 22.752,
+      "eval_steps_per_second": 2.844,
+      "step": 440
+    },
+    {
+      "epoch": 6.0,
+      "grad_norm": 3.1378376483917236,
+      "learning_rate": 2.6666666666666667e-05,
+      "loss": 1.7966,
+      "step": 450
+    },
+    {
+      "epoch": 6.0,
+      "eval_loss": 2.8000402450561523,
+      "eval_runtime": 43.9182,
+      "eval_samples_per_second": 22.77,
+      "eval_steps_per_second": 2.846,
+      "step": 450
+    },
+    {
+      "epoch": 6.133333333333334,
+      "grad_norm": 3.289393424987793,
+      "learning_rate": 2.5481481481481484e-05,
+      "loss": 1.7021,
+      "step": 460
+    },
+    {
+      "epoch": 6.133333333333334,
+      "eval_loss": 2.8974051475524902,
+      "eval_runtime": 43.8673,
+      "eval_samples_per_second": 22.796,
+      "eval_steps_per_second": 2.85,
+      "step": 460
+    },
+    {
+      "epoch": 6.266666666666667,
+      "grad_norm": 3.662322998046875,
+      "learning_rate": 2.4296296296296298e-05,
+      "loss": 1.6801,
+      "step": 470
+    },
+    {
+      "epoch": 6.266666666666667,
+      "eval_loss": 2.891542911529541,
+      "eval_runtime": 43.9675,
+      "eval_samples_per_second": 22.744,
+      "eval_steps_per_second": 2.843,
+      "step": 470
+    },
+    {
+      "epoch": 6.4,
+      "grad_norm": 3.6940433979034424,
+      "learning_rate": 2.3111111111111112e-05,
+      "loss": 1.6549,
+      "step": 480
+    },
+    {
+      "epoch": 6.4,
+      "eval_loss": 2.884908676147461,
+      "eval_runtime": 43.9337,
+      "eval_samples_per_second": 22.762,
+      "eval_steps_per_second": 2.845,
+      "step": 480
+    },
+    {
+      "epoch": 6.533333333333333,
+      "grad_norm": 3.8792476654052734,
+      "learning_rate": 2.192592592592593e-05,
+      "loss": 1.6964,
+      "step": 490
+    },
+    {
+      "epoch": 6.533333333333333,
+      "eval_loss": 2.8918919563293457,
+      "eval_runtime": 43.9143,
+      "eval_samples_per_second": 22.772,
+      "eval_steps_per_second": 2.846,
+      "step": 490
+    },
+    {
+      "epoch": 6.666666666666667,
+      "grad_norm": 3.8439388275146484,
+      "learning_rate": 2.074074074074074e-05,
+      "loss": 1.7524,
+      "step": 500
+    },
+    {
+      "epoch": 6.666666666666667,
+      "eval_loss": 2.890720844268799,
+      "eval_runtime": 43.9225,
+      "eval_samples_per_second": 22.767,
+      "eval_steps_per_second": 2.846,
+      "step": 500
+    },
+    {
+      "epoch": 6.8,
+      "grad_norm": 3.7934892177581787,
+      "learning_rate": 1.9555555555555557e-05,
+      "loss": 1.7211,
+      "step": 510
+    },
+    {
+      "epoch": 6.8,
+      "eval_loss": 2.8894593715667725,
+      "eval_runtime": 43.9778,
+      "eval_samples_per_second": 22.739,
+      "eval_steps_per_second": 2.842,
+      "step": 510
+    },
+    {
+      "epoch": 6.933333333333334,
+      "grad_norm": 3.739837884902954,
+      "learning_rate": 1.837037037037037e-05,
+      "loss": 1.6917,
+      "step": 520
+    },
+    {
+      "epoch": 6.933333333333334,
+      "eval_loss": 2.8792428970336914,
+      "eval_runtime": 43.9841,
+      "eval_samples_per_second": 22.735,
+      "eval_steps_per_second": 2.842,
+      "step": 520
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 8.52075743281152e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-530/README.md

@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-530/adapter_config.json

@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "dense_h_to_4h",
+    "query_key_value",
+    "dense",
+    "dense_4h_to_h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-530/trainer_state.json

@@ -0,0 +1,828 @@
+{
+  "best_metric": 2.5317564010620117,
+  "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
+  "epoch": 7.066666666666666,
+  "eval_steps": 10,
+  "global_step": 530,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.4347652792930603,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 2.4954,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 2.556234359741211,
+      "eval_runtime": 43.818,
+      "eval_samples_per_second": 22.822,
+      "eval_steps_per_second": 2.853,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.40230727195739746,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 2.5574,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 2.552377462387085,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3980488181114197,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 2.4669,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 2.549164056777954,
+      "eval_runtime": 43.8389,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.4006142020225525,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 2.5199,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 2.546046495437622,
+      "eval_runtime": 43.8456,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.4202616512775421,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 2.5619,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 2.5431504249572754,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3871513307094574,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 2.5057,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 2.5413730144500732,
+      "eval_runtime": 43.8646,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.36390039324760437,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 2.4606,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 2.5389301776885986,
+      "eval_runtime": 43.8837,
+      "eval_samples_per_second": 22.788,
+      "eval_steps_per_second": 2.848,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.4081075191497803,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 2.4696,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 2.5368435382843018,
+      "eval_runtime": 43.8696,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.5448070764541626,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 2.4258,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 2.538212776184082,
+      "eval_runtime": 43.8585,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.7155500650405884,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 2.4865,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 2.540060043334961,
+      "eval_runtime": 43.8337,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.7326843738555908,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 2.4391,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 2.5385019779205322,
+      "eval_runtime": 43.8789,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.8026068806648254,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 2.4001,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 2.5356342792510986,
+      "eval_runtime": 43.8699,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.8492558598518372,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 2.387,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 2.5329699516296387,
+      "eval_runtime": 43.8654,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 1.1200364828109741,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 2.3817,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 2.5319204330444336,
+      "eval_runtime": 43.847,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.9766451120376587,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 2.4193,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 2.5317564010620117,
+      "eval_runtime": 43.8504,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 1.0703226327896118,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 2.3341,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 2.5564167499542236,
+      "eval_runtime": 43.8299,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.3115178346633911,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 2.2182,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 2.5810468196868896,
+      "eval_runtime": 43.8366,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.4998687505722046,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 2.2379,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 2.580641269683838,
+      "eval_runtime": 43.8362,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.6269217729568481,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 2.2346,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 2.572070360183716,
+      "eval_runtime": 43.8376,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.5595163106918335,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 2.225,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 2.574326276779175,
+      "eval_runtime": 43.8537,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.673547387123108,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 2.2471,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 2.5765159130096436,
+      "eval_runtime": 43.8369,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 1.5295490026474,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 2.204,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 2.5766921043395996,
+      "eval_runtime": 43.8443,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 1.6709380149841309,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 2.1753,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 2.602360248565674,
+      "eval_runtime": 43.8576,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 2.053478240966797,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 2.0405,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 2.6636874675750732,
+      "eval_runtime": 43.8509,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.8616771697998047,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 2.0265,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 2.6536307334899902,
+      "eval_runtime": 43.8433,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 2.1498146057128906,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 2.1386,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 2.658257246017456,
+      "eval_runtime": 43.8516,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.851,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 2.203857660293579,
+      "learning_rate": 4.8e-05,
+      "loss": 2.0367,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 2.658139228820801,
+      "eval_runtime": 43.8709,
+      "eval_samples_per_second": 22.794,
+      "eval_steps_per_second": 2.849,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 2.0805578231811523,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 2.0226,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 2.646563768386841,
+      "eval_runtime": 43.8726,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 2.27193546295166,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 2.1099,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 2.6486735343933105,
+      "eval_runtime": 43.881,
+      "eval_samples_per_second": 22.789,
+      "eval_steps_per_second": 2.849,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 2.0627055168151855,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 2.0996,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 2.644541025161743,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 2.6526894569396973,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.8896,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 2.7607998847961426,
+      "eval_runtime": 43.8953,
+      "eval_samples_per_second": 22.781,
+      "eval_steps_per_second": 2.848,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 2.813822031021118,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.8568,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 2.7357044219970703,
+      "eval_runtime": 43.8795,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 3.134248733520508,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.9636,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 2.742431640625,
+      "eval_runtime": 43.8639,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 2.727226495742798,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.9148,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 2.7314682006835938,
+      "eval_runtime": 43.852,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.85,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 2.768984079360962,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.9134,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 2.7299180030822754,
+      "eval_runtime": 43.8498,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 350
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 3.0203487873077393,
+      "learning_rate": 3.733333333333334e-05,
+      "loss": 1.9445,
+      "step": 360
+    },
+    {
+      "epoch": 4.8,
+      "eval_loss": 2.7333309650421143,
+      "eval_runtime": 43.8634,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 360
+    },
+    {
+      "epoch": 4.933333333333334,
+      "grad_norm": 2.721759080886841,
+      "learning_rate": 3.614814814814815e-05,
+      "loss": 1.9199,
+      "step": 370
+    },
+    {
+      "epoch": 4.933333333333334,
+      "eval_loss": 2.7230074405670166,
+      "eval_runtime": 43.8351,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 370
+    },
+    {
+      "epoch": 5.066666666666666,
+      "grad_norm": 2.812037467956543,
+      "learning_rate": 3.4962962962962965e-05,
+      "loss": 1.9396,
+      "step": 380
+    },
+    {
+      "epoch": 5.066666666666666,
+      "eval_loss": 2.7738075256347656,
+      "eval_runtime": 43.8405,
+      "eval_samples_per_second": 22.81,
+      "eval_steps_per_second": 2.851,
+      "step": 380
+    },
+    {
+      "epoch": 5.2,
+      "grad_norm": 3.347679376602173,
+      "learning_rate": 3.377777777777778e-05,
+      "loss": 1.8374,
+      "step": 390
+    },
+    {
+      "epoch": 5.2,
+      "eval_loss": 2.830467700958252,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 390
+    },
+    {
+      "epoch": 5.333333333333333,
+      "grad_norm": 3.1343460083007812,
+      "learning_rate": 3.259259259259259e-05,
+      "loss": 1.7472,
+      "step": 400
+    },
+    {
+      "epoch": 5.333333333333333,
+      "eval_loss": 2.8105757236480713,
+      "eval_runtime": 43.9522,
+      "eval_samples_per_second": 22.752,
+      "eval_steps_per_second": 2.844,
+      "step": 400
+    },
+    {
+      "epoch": 5.466666666666667,
+      "grad_norm": 3.431727170944214,
+      "learning_rate": 3.140740740740741e-05,
+      "loss": 1.8274,
+      "step": 410
+    },
+    {
+      "epoch": 5.466666666666667,
+      "eval_loss": 2.816023826599121,
+      "eval_runtime": 43.9615,
+      "eval_samples_per_second": 22.747,
+      "eval_steps_per_second": 2.843,
+      "step": 410
+    },
+    {
+      "epoch": 5.6,
+      "grad_norm": 3.4572854042053223,
+      "learning_rate": 3.0222222222222225e-05,
+      "loss": 1.8135,
+      "step": 420
+    },
+    {
+      "epoch": 5.6,
+      "eval_loss": 2.817023992538452,
+      "eval_runtime": 43.9443,
+      "eval_samples_per_second": 22.756,
+      "eval_steps_per_second": 2.845,
+      "step": 420
+    },
+    {
+      "epoch": 5.733333333333333,
+      "grad_norm": 3.286614179611206,
+      "learning_rate": 2.9037037037037042e-05,
+      "loss": 1.8312,
+      "step": 430
+    },
+    {
+      "epoch": 5.733333333333333,
+      "eval_loss": 2.813601493835449,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 430
+    },
+    {
+      "epoch": 5.866666666666667,
+      "grad_norm": 3.152069568634033,
+      "learning_rate": 2.7851851851851856e-05,
+      "loss": 1.7372,
+      "step": 440
+    },
+    {
+      "epoch": 5.866666666666667,
+      "eval_loss": 2.8068931102752686,
+      "eval_runtime": 43.9514,
+      "eval_samples_per_second": 22.752,
+      "eval_steps_per_second": 2.844,
+      "step": 440
+    },
+    {
+      "epoch": 6.0,
+      "grad_norm": 3.1378376483917236,
+      "learning_rate": 2.6666666666666667e-05,
+      "loss": 1.7966,
+      "step": 450
+    },
+    {
+      "epoch": 6.0,
+      "eval_loss": 2.8000402450561523,
+      "eval_runtime": 43.9182,
+      "eval_samples_per_second": 22.77,
+      "eval_steps_per_second": 2.846,
+      "step": 450
+    },
+    {
+      "epoch": 6.133333333333334,
+      "grad_norm": 3.289393424987793,
+      "learning_rate": 2.5481481481481484e-05,
+      "loss": 1.7021,
+      "step": 460
+    },
+    {
+      "epoch": 6.133333333333334,
+      "eval_loss": 2.8974051475524902,
+      "eval_runtime": 43.8673,
+      "eval_samples_per_second": 22.796,
+      "eval_steps_per_second": 2.85,
+      "step": 460
+    },
+    {
+      "epoch": 6.266666666666667,
+      "grad_norm": 3.662322998046875,
+      "learning_rate": 2.4296296296296298e-05,
+      "loss": 1.6801,
+      "step": 470
+    },
+    {
+      "epoch": 6.266666666666667,
+      "eval_loss": 2.891542911529541,
+      "eval_runtime": 43.9675,
+      "eval_samples_per_second": 22.744,
+      "eval_steps_per_second": 2.843,
+      "step": 470
+    },
+    {
+      "epoch": 6.4,
+      "grad_norm": 3.6940433979034424,
+      "learning_rate": 2.3111111111111112e-05,
+      "loss": 1.6549,
+      "step": 480
+    },
+    {
+      "epoch": 6.4,
+      "eval_loss": 2.884908676147461,
+      "eval_runtime": 43.9337,
+      "eval_samples_per_second": 22.762,
+      "eval_steps_per_second": 2.845,
+      "step": 480
+    },
+    {
+      "epoch": 6.533333333333333,
+      "grad_norm": 3.8792476654052734,
+      "learning_rate": 2.192592592592593e-05,
+      "loss": 1.6964,
+      "step": 490
+    },
+    {
+      "epoch": 6.533333333333333,
+      "eval_loss": 2.8918919563293457,
+      "eval_runtime": 43.9143,
+      "eval_samples_per_second": 22.772,
+      "eval_steps_per_second": 2.846,
+      "step": 490
+    },
+    {
+      "epoch": 6.666666666666667,
+      "grad_norm": 3.8439388275146484,
+      "learning_rate": 2.074074074074074e-05,
+      "loss": 1.7524,
+      "step": 500
+    },
+    {
+      "epoch": 6.666666666666667,
+      "eval_loss": 2.890720844268799,
+      "eval_runtime": 43.9225,
+      "eval_samples_per_second": 22.767,
+      "eval_steps_per_second": 2.846,
+      "step": 500
+    },
+    {
+      "epoch": 6.8,
+      "grad_norm": 3.7934892177581787,
+      "learning_rate": 1.9555555555555557e-05,
+      "loss": 1.7211,
+      "step": 510
+    },
+    {
+      "epoch": 6.8,
+      "eval_loss": 2.8894593715667725,
+      "eval_runtime": 43.9778,
+      "eval_samples_per_second": 22.739,
+      "eval_steps_per_second": 2.842,
+      "step": 510
+    },
+    {
+      "epoch": 6.933333333333334,
+      "grad_norm": 3.739837884902954,
+      "learning_rate": 1.837037037037037e-05,
+      "loss": 1.6917,
+      "step": 520
+    },
+    {
+      "epoch": 6.933333333333334,
+      "eval_loss": 2.8792428970336914,
+      "eval_runtime": 43.9841,
+      "eval_samples_per_second": 22.735,
+      "eval_steps_per_second": 2.842,
+      "step": 520
+    },
+    {
+      "epoch": 7.066666666666666,
+      "grad_norm": 3.616173267364502,
+      "learning_rate": 1.7185185185185185e-05,
+      "loss": 1.7032,
+      "step": 530
+    },
+    {
+      "epoch": 7.066666666666666,
+      "eval_loss": 2.9059717655181885,
+      "eval_runtime": 43.9541,
+      "eval_samples_per_second": 22.751,
+      "eval_steps_per_second": 2.844,
+      "step": 530
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 8.68461815267328e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-540/README.md

@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-540/adapter_config.json

@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "dense_h_to_4h",
+    "query_key_value",
+    "dense",
+    "dense_4h_to_h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-540/trainer_state.json

@@ -0,0 +1,843 @@
+{
+  "best_metric": 2.5317564010620117,
+  "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
+  "epoch": 7.2,
+  "eval_steps": 10,
+  "global_step": 540,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.4347652792930603,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 2.4954,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 2.556234359741211,
+      "eval_runtime": 43.818,
+      "eval_samples_per_second": 22.822,
+      "eval_steps_per_second": 2.853,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.40230727195739746,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 2.5574,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 2.552377462387085,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3980488181114197,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 2.4669,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 2.549164056777954,
+      "eval_runtime": 43.8389,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.4006142020225525,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 2.5199,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 2.546046495437622,
+      "eval_runtime": 43.8456,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.4202616512775421,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 2.5619,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 2.5431504249572754,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3871513307094574,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 2.5057,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 2.5413730144500732,
+      "eval_runtime": 43.8646,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.36390039324760437,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 2.4606,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 2.5389301776885986,
+      "eval_runtime": 43.8837,
+      "eval_samples_per_second": 22.788,
+      "eval_steps_per_second": 2.848,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.4081075191497803,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 2.4696,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 2.5368435382843018,
+      "eval_runtime": 43.8696,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.5448070764541626,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 2.4258,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 2.538212776184082,
+      "eval_runtime": 43.8585,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.7155500650405884,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 2.4865,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 2.540060043334961,
+      "eval_runtime": 43.8337,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.7326843738555908,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 2.4391,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 2.5385019779205322,
+      "eval_runtime": 43.8789,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.8026068806648254,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 2.4001,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 2.5356342792510986,
+      "eval_runtime": 43.8699,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.8492558598518372,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 2.387,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 2.5329699516296387,
+      "eval_runtime": 43.8654,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 1.1200364828109741,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 2.3817,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 2.5319204330444336,
+      "eval_runtime": 43.847,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.9766451120376587,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 2.4193,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 2.5317564010620117,
+      "eval_runtime": 43.8504,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 1.0703226327896118,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 2.3341,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 2.5564167499542236,
+      "eval_runtime": 43.8299,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.3115178346633911,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 2.2182,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 2.5810468196868896,
+      "eval_runtime": 43.8366,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.4998687505722046,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 2.2379,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 2.580641269683838,
+      "eval_runtime": 43.8362,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.6269217729568481,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 2.2346,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 2.572070360183716,
+      "eval_runtime": 43.8376,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.5595163106918335,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 2.225,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 2.574326276779175,
+      "eval_runtime": 43.8537,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.673547387123108,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 2.2471,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 2.5765159130096436,
+      "eval_runtime": 43.8369,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 1.5295490026474,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 2.204,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 2.5766921043395996,
+      "eval_runtime": 43.8443,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 1.6709380149841309,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 2.1753,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 2.602360248565674,
+      "eval_runtime": 43.8576,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 2.053478240966797,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 2.0405,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 2.6636874675750732,
+      "eval_runtime": 43.8509,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.8616771697998047,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 2.0265,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 2.6536307334899902,
+      "eval_runtime": 43.8433,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 2.1498146057128906,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 2.1386,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 2.658257246017456,
+      "eval_runtime": 43.8516,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.851,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 2.203857660293579,
+      "learning_rate": 4.8e-05,
+      "loss": 2.0367,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 2.658139228820801,
+      "eval_runtime": 43.8709,
+      "eval_samples_per_second": 22.794,
+      "eval_steps_per_second": 2.849,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 2.0805578231811523,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 2.0226,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 2.646563768386841,
+      "eval_runtime": 43.8726,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 2.27193546295166,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 2.1099,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 2.6486735343933105,
+      "eval_runtime": 43.881,
+      "eval_samples_per_second": 22.789,
+      "eval_steps_per_second": 2.849,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 2.0627055168151855,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 2.0996,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 2.644541025161743,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 2.6526894569396973,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.8896,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 2.7607998847961426,
+      "eval_runtime": 43.8953,
+      "eval_samples_per_second": 22.781,
+      "eval_steps_per_second": 2.848,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 2.813822031021118,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.8568,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 2.7357044219970703,
+      "eval_runtime": 43.8795,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 3.134248733520508,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.9636,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 2.742431640625,
+      "eval_runtime": 43.8639,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 2.727226495742798,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.9148,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 2.7314682006835938,
+      "eval_runtime": 43.852,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.85,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 2.768984079360962,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.9134,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 2.7299180030822754,
+      "eval_runtime": 43.8498,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 350
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 3.0203487873077393,
+      "learning_rate": 3.733333333333334e-05,
+      "loss": 1.9445,
+      "step": 360
+    },
+    {
+      "epoch": 4.8,
+      "eval_loss": 2.7333309650421143,
+      "eval_runtime": 43.8634,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 360
+    },
+    {
+      "epoch": 4.933333333333334,
+      "grad_norm": 2.721759080886841,
+      "learning_rate": 3.614814814814815e-05,
+      "loss": 1.9199,
+      "step": 370
+    },
+    {
+      "epoch": 4.933333333333334,
+      "eval_loss": 2.7230074405670166,
+      "eval_runtime": 43.8351,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 370
+    },
+    {
+      "epoch": 5.066666666666666,
+      "grad_norm": 2.812037467956543,
+      "learning_rate": 3.4962962962962965e-05,
+      "loss": 1.9396,
+      "step": 380
+    },
+    {
+      "epoch": 5.066666666666666,
+      "eval_loss": 2.7738075256347656,
+      "eval_runtime": 43.8405,
+      "eval_samples_per_second": 22.81,
+      "eval_steps_per_second": 2.851,
+      "step": 380
+    },
+    {
+      "epoch": 5.2,
+      "grad_norm": 3.347679376602173,
+      "learning_rate": 3.377777777777778e-05,
+      "loss": 1.8374,
+      "step": 390
+    },
+    {
+      "epoch": 5.2,
+      "eval_loss": 2.830467700958252,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 390
+    },
+    {
+      "epoch": 5.333333333333333,
+      "grad_norm": 3.1343460083007812,
+      "learning_rate": 3.259259259259259e-05,
+      "loss": 1.7472,
+      "step": 400
+    },
+    {
+      "epoch": 5.333333333333333,
+      "eval_loss": 2.8105757236480713,
+      "eval_runtime": 43.9522,
+      "eval_samples_per_second": 22.752,
+      "eval_steps_per_second": 2.844,
+      "step": 400
+    },
+    {
+      "epoch": 5.466666666666667,
+      "grad_norm": 3.431727170944214,
+      "learning_rate": 3.140740740740741e-05,
+      "loss": 1.8274,
+      "step": 410
+    },
+    {
+      "epoch": 5.466666666666667,
+      "eval_loss": 2.816023826599121,
+      "eval_runtime": 43.9615,
+      "eval_samples_per_second": 22.747,
+      "eval_steps_per_second": 2.843,
+      "step": 410
+    },
+    {
+      "epoch": 5.6,
+      "grad_norm": 3.4572854042053223,
+      "learning_rate": 3.0222222222222225e-05,
+      "loss": 1.8135,
+      "step": 420
+    },
+    {
+      "epoch": 5.6,
+      "eval_loss": 2.817023992538452,
+      "eval_runtime": 43.9443,
+      "eval_samples_per_second": 22.756,
+      "eval_steps_per_second": 2.845,
+      "step": 420
+    },
+    {
+      "epoch": 5.733333333333333,
+      "grad_norm": 3.286614179611206,
+      "learning_rate": 2.9037037037037042e-05,
+      "loss": 1.8312,
+      "step": 430
+    },
+    {
+      "epoch": 5.733333333333333,
+      "eval_loss": 2.813601493835449,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 430
+    },
+    {
+      "epoch": 5.866666666666667,
+      "grad_norm": 3.152069568634033,
+      "learning_rate": 2.7851851851851856e-05,
+      "loss": 1.7372,
+      "step": 440
+    },
+    {
+      "epoch": 5.866666666666667,
+      "eval_loss": 2.8068931102752686,
+      "eval_runtime": 43.9514,
+      "eval_samples_per_second": 22.752,
+      "eval_steps_per_second": 2.844,
+      "step": 440
+    },
+    {
+      "epoch": 6.0,
+      "grad_norm": 3.1378376483917236,
+      "learning_rate": 2.6666666666666667e-05,
+      "loss": 1.7966,
+      "step": 450
+    },
+    {
+      "epoch": 6.0,
+      "eval_loss": 2.8000402450561523,
+      "eval_runtime": 43.9182,
+      "eval_samples_per_second": 22.77,
+      "eval_steps_per_second": 2.846,
+      "step": 450
+    },
+    {
+      "epoch": 6.133333333333334,
+      "grad_norm": 3.289393424987793,
+      "learning_rate": 2.5481481481481484e-05,
+      "loss": 1.7021,
+      "step": 460
+    },
+    {
+      "epoch": 6.133333333333334,
+      "eval_loss": 2.8974051475524902,
+      "eval_runtime": 43.8673,
+      "eval_samples_per_second": 22.796,
+      "eval_steps_per_second": 2.85,
+      "step": 460
+    },
+    {
+      "epoch": 6.266666666666667,
+      "grad_norm": 3.662322998046875,
+      "learning_rate": 2.4296296296296298e-05,
+      "loss": 1.6801,
+      "step": 470
+    },
+    {
+      "epoch": 6.266666666666667,
+      "eval_loss": 2.891542911529541,
+      "eval_runtime": 43.9675,
+      "eval_samples_per_second": 22.744,
+      "eval_steps_per_second": 2.843,
+      "step": 470
+    },
+    {
+      "epoch": 6.4,
+      "grad_norm": 3.6940433979034424,
+      "learning_rate": 2.3111111111111112e-05,
+      "loss": 1.6549,
+      "step": 480
+    },
+    {
+      "epoch": 6.4,
+      "eval_loss": 2.884908676147461,
+      "eval_runtime": 43.9337,
+      "eval_samples_per_second": 22.762,
+      "eval_steps_per_second": 2.845,
+      "step": 480
+    },
+    {
+      "epoch": 6.533333333333333,
+      "grad_norm": 3.8792476654052734,
+      "learning_rate": 2.192592592592593e-05,
+      "loss": 1.6964,
+      "step": 490
+    },
+    {
+      "epoch": 6.533333333333333,
+      "eval_loss": 2.8918919563293457,
+      "eval_runtime": 43.9143,
+      "eval_samples_per_second": 22.772,
+      "eval_steps_per_second": 2.846,
+      "step": 490
+    },
+    {
+      "epoch": 6.666666666666667,
+      "grad_norm": 3.8439388275146484,
+      "learning_rate": 2.074074074074074e-05,
+      "loss": 1.7524,
+      "step": 500
+    },
+    {
+      "epoch": 6.666666666666667,
+      "eval_loss": 2.890720844268799,
+      "eval_runtime": 43.9225,
+      "eval_samples_per_second": 22.767,
+      "eval_steps_per_second": 2.846,
+      "step": 500
+    },
+    {
+      "epoch": 6.8,
+      "grad_norm": 3.7934892177581787,
+      "learning_rate": 1.9555555555555557e-05,
+      "loss": 1.7211,
+      "step": 510
+    },
+    {
+      "epoch": 6.8,
+      "eval_loss": 2.8894593715667725,
+      "eval_runtime": 43.9778,
+      "eval_samples_per_second": 22.739,
+      "eval_steps_per_second": 2.842,
+      "step": 510
+    },
+    {
+      "epoch": 6.933333333333334,
+      "grad_norm": 3.739837884902954,
+      "learning_rate": 1.837037037037037e-05,
+      "loss": 1.6917,
+      "step": 520
+    },
+    {
+      "epoch": 6.933333333333334,
+      "eval_loss": 2.8792428970336914,
+      "eval_runtime": 43.9841,
+      "eval_samples_per_second": 22.735,
+      "eval_steps_per_second": 2.842,
+      "step": 520
+    },
+    {
+      "epoch": 7.066666666666666,
+      "grad_norm": 3.616173267364502,
+      "learning_rate": 1.7185185185185185e-05,
+      "loss": 1.7032,
+      "step": 530
+    },
+    {
+      "epoch": 7.066666666666666,
+      "eval_loss": 2.9059717655181885,
+      "eval_runtime": 43.9541,
+      "eval_samples_per_second": 22.751,
+      "eval_steps_per_second": 2.844,
+      "step": 530
+    },
+    {
+      "epoch": 7.2,
+      "grad_norm": 4.411597728729248,
+      "learning_rate": 1.6000000000000003e-05,
+      "loss": 1.5858,
+      "step": 540
+    },
+    {
+      "epoch": 7.2,
+      "eval_loss": 2.969313859939575,
+      "eval_runtime": 43.9721,
+      "eval_samples_per_second": 22.742,
+      "eval_steps_per_second": 2.843,
+      "step": 540
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 8.84847887253504e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-550/README.md

@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-550/adapter_config.json

@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "dense_h_to_4h",
+    "query_key_value",
+    "dense",
+    "dense_4h_to_h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-550/trainer_state.json

@@ -0,0 +1,858 @@
+{
+  "best_metric": 2.5317564010620117,
+  "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
+  "epoch": 7.333333333333333,
+  "eval_steps": 10,
+  "global_step": 550,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.4347652792930603,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 2.4954,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 2.556234359741211,
+      "eval_runtime": 43.818,
+      "eval_samples_per_second": 22.822,
+      "eval_steps_per_second": 2.853,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.40230727195739746,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 2.5574,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 2.552377462387085,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3980488181114197,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 2.4669,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 2.549164056777954,
+      "eval_runtime": 43.8389,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.4006142020225525,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 2.5199,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 2.546046495437622,
+      "eval_runtime": 43.8456,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.4202616512775421,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 2.5619,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 2.5431504249572754,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3871513307094574,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 2.5057,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 2.5413730144500732,
+      "eval_runtime": 43.8646,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.36390039324760437,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 2.4606,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 2.5389301776885986,
+      "eval_runtime": 43.8837,
+      "eval_samples_per_second": 22.788,
+      "eval_steps_per_second": 2.848,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.4081075191497803,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 2.4696,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 2.5368435382843018,
+      "eval_runtime": 43.8696,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.5448070764541626,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 2.4258,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 2.538212776184082,
+      "eval_runtime": 43.8585,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.7155500650405884,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 2.4865,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 2.540060043334961,
+      "eval_runtime": 43.8337,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.7326843738555908,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 2.4391,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 2.5385019779205322,
+      "eval_runtime": 43.8789,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.8026068806648254,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 2.4001,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 2.5356342792510986,
+      "eval_runtime": 43.8699,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.8492558598518372,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 2.387,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 2.5329699516296387,
+      "eval_runtime": 43.8654,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 1.1200364828109741,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 2.3817,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 2.5319204330444336,
+      "eval_runtime": 43.847,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.9766451120376587,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 2.4193,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 2.5317564010620117,
+      "eval_runtime": 43.8504,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 1.0703226327896118,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 2.3341,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 2.5564167499542236,
+      "eval_runtime": 43.8299,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.3115178346633911,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 2.2182,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 2.5810468196868896,
+      "eval_runtime": 43.8366,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.4998687505722046,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 2.2379,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 2.580641269683838,
+      "eval_runtime": 43.8362,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.6269217729568481,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 2.2346,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 2.572070360183716,
+      "eval_runtime": 43.8376,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.5595163106918335,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 2.225,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 2.574326276779175,
+      "eval_runtime": 43.8537,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.673547387123108,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 2.2471,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 2.5765159130096436,
+      "eval_runtime": 43.8369,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 1.5295490026474,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 2.204,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 2.5766921043395996,
+      "eval_runtime": 43.8443,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 1.6709380149841309,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 2.1753,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 2.602360248565674,
+      "eval_runtime": 43.8576,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 2.053478240966797,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 2.0405,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 2.6636874675750732,
+      "eval_runtime": 43.8509,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.8616771697998047,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 2.0265,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 2.6536307334899902,
+      "eval_runtime": 43.8433,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 2.1498146057128906,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 2.1386,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 2.658257246017456,
+      "eval_runtime": 43.8516,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.851,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 2.203857660293579,
+      "learning_rate": 4.8e-05,
+      "loss": 2.0367,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 2.658139228820801,
+      "eval_runtime": 43.8709,
+      "eval_samples_per_second": 22.794,
+      "eval_steps_per_second": 2.849,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 2.0805578231811523,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 2.0226,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 2.646563768386841,
+      "eval_runtime": 43.8726,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 2.27193546295166,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 2.1099,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 2.6486735343933105,
+      "eval_runtime": 43.881,
+      "eval_samples_per_second": 22.789,
+      "eval_steps_per_second": 2.849,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 2.0627055168151855,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 2.0996,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 2.644541025161743,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 2.6526894569396973,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.8896,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 2.7607998847961426,
+      "eval_runtime": 43.8953,
+      "eval_samples_per_second": 22.781,
+      "eval_steps_per_second": 2.848,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 2.813822031021118,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.8568,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 2.7357044219970703,
+      "eval_runtime": 43.8795,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 3.134248733520508,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.9636,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 2.742431640625,
+      "eval_runtime": 43.8639,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 2.727226495742798,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.9148,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 2.7314682006835938,
+      "eval_runtime": 43.852,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.85,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 2.768984079360962,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.9134,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 2.7299180030822754,
+      "eval_runtime": 43.8498,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 350
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 3.0203487873077393,
+      "learning_rate": 3.733333333333334e-05,
+      "loss": 1.9445,
+      "step": 360
+    },
+    {
+      "epoch": 4.8,
+      "eval_loss": 2.7333309650421143,
+      "eval_runtime": 43.8634,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 360
+    },
+    {
+      "epoch": 4.933333333333334,
+      "grad_norm": 2.721759080886841,
+      "learning_rate": 3.614814814814815e-05,
+      "loss": 1.9199,
+      "step": 370
+    },
+    {
+      "epoch": 4.933333333333334,
+      "eval_loss": 2.7230074405670166,
+      "eval_runtime": 43.8351,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 370
+    },
+    {
+      "epoch": 5.066666666666666,
+      "grad_norm": 2.812037467956543,
+      "learning_rate": 3.4962962962962965e-05,
+      "loss": 1.9396,
+      "step": 380
+    },
+    {
+      "epoch": 5.066666666666666,
+      "eval_loss": 2.7738075256347656,
+      "eval_runtime": 43.8405,
+      "eval_samples_per_second": 22.81,
+      "eval_steps_per_second": 2.851,
+      "step": 380
+    },
+    {
+      "epoch": 5.2,
+      "grad_norm": 3.347679376602173,
+      "learning_rate": 3.377777777777778e-05,
+      "loss": 1.8374,
+      "step": 390
+    },
+    {
+      "epoch": 5.2,
+      "eval_loss": 2.830467700958252,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 390
+    },
+    {
+      "epoch": 5.333333333333333,
+      "grad_norm": 3.1343460083007812,
+      "learning_rate": 3.259259259259259e-05,
+      "loss": 1.7472,
+      "step": 400
+    },
+    {
+      "epoch": 5.333333333333333,
+      "eval_loss": 2.8105757236480713,
+      "eval_runtime": 43.9522,
+      "eval_samples_per_second": 22.752,
+      "eval_steps_per_second": 2.844,
+      "step": 400
+    },
+    {
+      "epoch": 5.466666666666667,
+      "grad_norm": 3.431727170944214,
+      "learning_rate": 3.140740740740741e-05,
+      "loss": 1.8274,
+      "step": 410
+    },
+    {
+      "epoch": 5.466666666666667,
+      "eval_loss": 2.816023826599121,
+      "eval_runtime": 43.9615,
+      "eval_samples_per_second": 22.747,
+      "eval_steps_per_second": 2.843,
+      "step": 410
+    },
+    {
+      "epoch": 5.6,
+      "grad_norm": 3.4572854042053223,
+      "learning_rate": 3.0222222222222225e-05,
+      "loss": 1.8135,
+      "step": 420
+    },
+    {
+      "epoch": 5.6,
+      "eval_loss": 2.817023992538452,
+      "eval_runtime": 43.9443,
+      "eval_samples_per_second": 22.756,
+      "eval_steps_per_second": 2.845,
+      "step": 420
+    },
+    {
+      "epoch": 5.733333333333333,
+      "grad_norm": 3.286614179611206,
+      "learning_rate": 2.9037037037037042e-05,
+      "loss": 1.8312,
+      "step": 430
+    },
+    {
+      "epoch": 5.733333333333333,
+      "eval_loss": 2.813601493835449,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 430
+    },
+    {
+      "epoch": 5.866666666666667,
+      "grad_norm": 3.152069568634033,
+      "learning_rate": 2.7851851851851856e-05,
+      "loss": 1.7372,
+      "step": 440
+    },
+    {
+      "epoch": 5.866666666666667,
+      "eval_loss": 2.8068931102752686,
+      "eval_runtime": 43.9514,
+      "eval_samples_per_second": 22.752,
+      "eval_steps_per_second": 2.844,
+      "step": 440
+    },
+    {
+      "epoch": 6.0,
+      "grad_norm": 3.1378376483917236,
+      "learning_rate": 2.6666666666666667e-05,
+      "loss": 1.7966,
+      "step": 450
+    },
+    {
+      "epoch": 6.0,
+      "eval_loss": 2.8000402450561523,
+      "eval_runtime": 43.9182,
+      "eval_samples_per_second": 22.77,
+      "eval_steps_per_second": 2.846,
+      "step": 450
+    },
+    {
+      "epoch": 6.133333333333334,
+      "grad_norm": 3.289393424987793,
+      "learning_rate": 2.5481481481481484e-05,
+      "loss": 1.7021,
+      "step": 460
+    },
+    {
+      "epoch": 6.133333333333334,
+      "eval_loss": 2.8974051475524902,
+      "eval_runtime": 43.8673,
+      "eval_samples_per_second": 22.796,
+      "eval_steps_per_second": 2.85,
+      "step": 460
+    },
+    {
+      "epoch": 6.266666666666667,
+      "grad_norm": 3.662322998046875,
+      "learning_rate": 2.4296296296296298e-05,
+      "loss": 1.6801,
+      "step": 470
+    },
+    {
+      "epoch": 6.266666666666667,
+      "eval_loss": 2.891542911529541,
+      "eval_runtime": 43.9675,
+      "eval_samples_per_second": 22.744,
+      "eval_steps_per_second": 2.843,
+      "step": 470
+    },
+    {
+      "epoch": 6.4,
+      "grad_norm": 3.6940433979034424,
+      "learning_rate": 2.3111111111111112e-05,
+      "loss": 1.6549,
+      "step": 480
+    },
+    {
+      "epoch": 6.4,
+      "eval_loss": 2.884908676147461,
+      "eval_runtime": 43.9337,
+      "eval_samples_per_second": 22.762,
+      "eval_steps_per_second": 2.845,
+      "step": 480
+    },
+    {
+      "epoch": 6.533333333333333,
+      "grad_norm": 3.8792476654052734,
+      "learning_rate": 2.192592592592593e-05,
+      "loss": 1.6964,
+      "step": 490
+    },
+    {
+      "epoch": 6.533333333333333,
+      "eval_loss": 2.8918919563293457,
+      "eval_runtime": 43.9143,
+      "eval_samples_per_second": 22.772,
+      "eval_steps_per_second": 2.846,
+      "step": 490
+    },
+    {
+      "epoch": 6.666666666666667,
+      "grad_norm": 3.8439388275146484,
+      "learning_rate": 2.074074074074074e-05,
+      "loss": 1.7524,
+      "step": 500
+    },
+    {
+      "epoch": 6.666666666666667,
+      "eval_loss": 2.890720844268799,
+      "eval_runtime": 43.9225,
+      "eval_samples_per_second": 22.767,
+      "eval_steps_per_second": 2.846,
+      "step": 500
+    },
+    {
+      "epoch": 6.8,
+      "grad_norm": 3.7934892177581787,
+      "learning_rate": 1.9555555555555557e-05,
+      "loss": 1.7211,
+      "step": 510
+    },
+    {
+      "epoch": 6.8,
+      "eval_loss": 2.8894593715667725,
+      "eval_runtime": 43.9778,
+      "eval_samples_per_second": 22.739,
+      "eval_steps_per_second": 2.842,
+      "step": 510
+    },
+    {
+      "epoch": 6.933333333333334,
+      "grad_norm": 3.739837884902954,
+      "learning_rate": 1.837037037037037e-05,
+      "loss": 1.6917,
+      "step": 520
+    },
+    {
+      "epoch": 6.933333333333334,
+      "eval_loss": 2.8792428970336914,
+      "eval_runtime": 43.9841,
+      "eval_samples_per_second": 22.735,
+      "eval_steps_per_second": 2.842,
+      "step": 520
+    },
+    {
+      "epoch": 7.066666666666666,
+      "grad_norm": 3.616173267364502,
+      "learning_rate": 1.7185185185185185e-05,
+      "loss": 1.7032,
+      "step": 530
+    },
+    {
+      "epoch": 7.066666666666666,
+      "eval_loss": 2.9059717655181885,
+      "eval_runtime": 43.9541,
+      "eval_samples_per_second": 22.751,
+      "eval_steps_per_second": 2.844,
+      "step": 530
+    },
+    {
+      "epoch": 7.2,
+      "grad_norm": 4.411597728729248,
+      "learning_rate": 1.6000000000000003e-05,
+      "loss": 1.5858,
+      "step": 540
+    },
+    {
+      "epoch": 7.2,
+      "eval_loss": 2.969313859939575,
+      "eval_runtime": 43.9721,
+      "eval_samples_per_second": 22.742,
+      "eval_steps_per_second": 2.843,
+      "step": 540
+    },
+    {
+      "epoch": 7.333333333333333,
+      "grad_norm": 3.8424997329711914,
+      "learning_rate": 1.4814814814814815e-05,
+      "loss": 1.6097,
+      "step": 550
+    },
+    {
+      "epoch": 7.333333333333333,
+      "eval_loss": 2.9442644119262695,
+      "eval_runtime": 43.9947,
+      "eval_samples_per_second": 22.73,
+      "eval_steps_per_second": 2.841,
+      "step": 550
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 9.0123395923968e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-560/README.md

@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-560/adapter_config.json

@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "dense_h_to_4h",
+    "query_key_value",
+    "dense",
+    "dense_4h_to_h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-560/trainer_state.json

@@ -0,0 +1,873 @@
+{
+  "best_metric": 2.5317564010620117,
+  "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
+  "epoch": 7.466666666666667,
+  "eval_steps": 10,
+  "global_step": 560,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.4347652792930603,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 2.4954,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 2.556234359741211,
+      "eval_runtime": 43.818,
+      "eval_samples_per_second": 22.822,
+      "eval_steps_per_second": 2.853,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.40230727195739746,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 2.5574,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 2.552377462387085,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3980488181114197,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 2.4669,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 2.549164056777954,
+      "eval_runtime": 43.8389,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.4006142020225525,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 2.5199,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 2.546046495437622,
+      "eval_runtime": 43.8456,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.4202616512775421,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 2.5619,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 2.5431504249572754,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3871513307094574,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 2.5057,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 2.5413730144500732,
+      "eval_runtime": 43.8646,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.36390039324760437,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 2.4606,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 2.5389301776885986,
+      "eval_runtime": 43.8837,
+      "eval_samples_per_second": 22.788,
+      "eval_steps_per_second": 2.848,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.4081075191497803,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 2.4696,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 2.5368435382843018,
+      "eval_runtime": 43.8696,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.5448070764541626,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 2.4258,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 2.538212776184082,
+      "eval_runtime": 43.8585,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.7155500650405884,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 2.4865,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 2.540060043334961,
+      "eval_runtime": 43.8337,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.7326843738555908,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 2.4391,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 2.5385019779205322,
+      "eval_runtime": 43.8789,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.8026068806648254,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 2.4001,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 2.5356342792510986,
+      "eval_runtime": 43.8699,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.8492558598518372,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 2.387,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 2.5329699516296387,
+      "eval_runtime": 43.8654,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 1.1200364828109741,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 2.3817,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 2.5319204330444336,
+      "eval_runtime": 43.847,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.9766451120376587,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 2.4193,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 2.5317564010620117,
+      "eval_runtime": 43.8504,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 1.0703226327896118,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 2.3341,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 2.5564167499542236,
+      "eval_runtime": 43.8299,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.3115178346633911,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 2.2182,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 2.5810468196868896,
+      "eval_runtime": 43.8366,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.4998687505722046,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 2.2379,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 2.580641269683838,
+      "eval_runtime": 43.8362,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.6269217729568481,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 2.2346,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 2.572070360183716,
+      "eval_runtime": 43.8376,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.5595163106918335,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 2.225,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 2.574326276779175,
+      "eval_runtime": 43.8537,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.673547387123108,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 2.2471,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 2.5765159130096436,
+      "eval_runtime": 43.8369,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 1.5295490026474,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 2.204,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 2.5766921043395996,
+      "eval_runtime": 43.8443,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 1.6709380149841309,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 2.1753,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 2.602360248565674,
+      "eval_runtime": 43.8576,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 2.053478240966797,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 2.0405,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 2.6636874675750732,
+      "eval_runtime": 43.8509,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.8616771697998047,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 2.0265,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 2.6536307334899902,
+      "eval_runtime": 43.8433,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 2.1498146057128906,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 2.1386,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 2.658257246017456,
+      "eval_runtime": 43.8516,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.851,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 2.203857660293579,
+      "learning_rate": 4.8e-05,
+      "loss": 2.0367,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 2.658139228820801,
+      "eval_runtime": 43.8709,
+      "eval_samples_per_second": 22.794,
+      "eval_steps_per_second": 2.849,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 2.0805578231811523,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 2.0226,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 2.646563768386841,
+      "eval_runtime": 43.8726,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 2.27193546295166,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 2.1099,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 2.6486735343933105,
+      "eval_runtime": 43.881,
+      "eval_samples_per_second": 22.789,
+      "eval_steps_per_second": 2.849,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 2.0627055168151855,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 2.0996,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 2.644541025161743,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 2.6526894569396973,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.8896,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 2.7607998847961426,
+      "eval_runtime": 43.8953,
+      "eval_samples_per_second": 22.781,
+      "eval_steps_per_second": 2.848,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 2.813822031021118,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.8568,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 2.7357044219970703,
+      "eval_runtime": 43.8795,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 3.134248733520508,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.9636,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 2.742431640625,
+      "eval_runtime": 43.8639,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 2.727226495742798,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.9148,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 2.7314682006835938,
+      "eval_runtime": 43.852,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.85,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 2.768984079360962,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.9134,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 2.7299180030822754,
+      "eval_runtime": 43.8498,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 350
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 3.0203487873077393,
+      "learning_rate": 3.733333333333334e-05,
+      "loss": 1.9445,
+      "step": 360
+    },
+    {
+      "epoch": 4.8,
+      "eval_loss": 2.7333309650421143,
+      "eval_runtime": 43.8634,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 360
+    },
+    {
+      "epoch": 4.933333333333334,
+      "grad_norm": 2.721759080886841,
+      "learning_rate": 3.614814814814815e-05,
+      "loss": 1.9199,
+      "step": 370
+    },
+    {
+      "epoch": 4.933333333333334,
+      "eval_loss": 2.7230074405670166,
+      "eval_runtime": 43.8351,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 370
+    },
+    {
+      "epoch": 5.066666666666666,
+      "grad_norm": 2.812037467956543,
+      "learning_rate": 3.4962962962962965e-05,
+      "loss": 1.9396,
+      "step": 380
+    },
+    {
+      "epoch": 5.066666666666666,
+      "eval_loss": 2.7738075256347656,
+      "eval_runtime": 43.8405,
+      "eval_samples_per_second": 22.81,
+      "eval_steps_per_second": 2.851,
+      "step": 380
+    },
+    {
+      "epoch": 5.2,
+      "grad_norm": 3.347679376602173,
+      "learning_rate": 3.377777777777778e-05,
+      "loss": 1.8374,
+      "step": 390
+    },
+    {
+      "epoch": 5.2,
+      "eval_loss": 2.830467700958252,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 390
+    },
+    {
+      "epoch": 5.333333333333333,
+      "grad_norm": 3.1343460083007812,
+      "learning_rate": 3.259259259259259e-05,
+      "loss": 1.7472,
+      "step": 400
+    },
+    {
+      "epoch": 5.333333333333333,
+      "eval_loss": 2.8105757236480713,
+      "eval_runtime": 43.9522,
+      "eval_samples_per_second": 22.752,
+      "eval_steps_per_second": 2.844,
+      "step": 400
+    },
+    {
+      "epoch": 5.466666666666667,
+      "grad_norm": 3.431727170944214,
+      "learning_rate": 3.140740740740741e-05,
+      "loss": 1.8274,
+      "step": 410
+    },
+    {
+      "epoch": 5.466666666666667,
+      "eval_loss": 2.816023826599121,
+      "eval_runtime": 43.9615,
+      "eval_samples_per_second": 22.747,
+      "eval_steps_per_second": 2.843,
+      "step": 410
+    },
+    {
+      "epoch": 5.6,
+      "grad_norm": 3.4572854042053223,
+      "learning_rate": 3.0222222222222225e-05,
+      "loss": 1.8135,
+      "step": 420
+    },
+    {
+      "epoch": 5.6,
+      "eval_loss": 2.817023992538452,
+      "eval_runtime": 43.9443,
+      "eval_samples_per_second": 22.756,
+      "eval_steps_per_second": 2.845,
+      "step": 420
+    },
+    {
+      "epoch": 5.733333333333333,
+      "grad_norm": 3.286614179611206,
+      "learning_rate": 2.9037037037037042e-05,
+      "loss": 1.8312,
+      "step": 430
+    },
+    {
+      "epoch": 5.733333333333333,
+      "eval_loss": 2.813601493835449,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 430
+    },
+    {
+      "epoch": 5.866666666666667,
+      "grad_norm": 3.152069568634033,
+      "learning_rate": 2.7851851851851856e-05,
+      "loss": 1.7372,
+      "step": 440
+    },
+    {
+      "epoch": 5.866666666666667,
+      "eval_loss": 2.8068931102752686,
+      "eval_runtime": 43.9514,
+      "eval_samples_per_second": 22.752,
+      "eval_steps_per_second": 2.844,
+      "step": 440
+    },
+    {
+      "epoch": 6.0,
+      "grad_norm": 3.1378376483917236,
+      "learning_rate": 2.6666666666666667e-05,
+      "loss": 1.7966,
+      "step": 450
+    },
+    {
+      "epoch": 6.0,
+      "eval_loss": 2.8000402450561523,
+      "eval_runtime": 43.9182,
+      "eval_samples_per_second": 22.77,
+      "eval_steps_per_second": 2.846,
+      "step": 450
+    },
+    {
+      "epoch": 6.133333333333334,
+      "grad_norm": 3.289393424987793,
+      "learning_rate": 2.5481481481481484e-05,
+      "loss": 1.7021,
+      "step": 460
+    },
+    {
+      "epoch": 6.133333333333334,
+      "eval_loss": 2.8974051475524902,
+      "eval_runtime": 43.8673,
+      "eval_samples_per_second": 22.796,
+      "eval_steps_per_second": 2.85,
+      "step": 460
+    },
+    {
+      "epoch": 6.266666666666667,
+      "grad_norm": 3.662322998046875,
+      "learning_rate": 2.4296296296296298e-05,
+      "loss": 1.6801,
+      "step": 470
+    },
+    {
+      "epoch": 6.266666666666667,
+      "eval_loss": 2.891542911529541,
+      "eval_runtime": 43.9675,
+      "eval_samples_per_second": 22.744,
+      "eval_steps_per_second": 2.843,
+      "step": 470
+    },
+    {
+      "epoch": 6.4,
+      "grad_norm": 3.6940433979034424,
+      "learning_rate": 2.3111111111111112e-05,
+      "loss": 1.6549,
+      "step": 480
+    },
+    {
+      "epoch": 6.4,
+      "eval_loss": 2.884908676147461,
+      "eval_runtime": 43.9337,
+      "eval_samples_per_second": 22.762,
+      "eval_steps_per_second": 2.845,
+      "step": 480
+    },
+    {
+      "epoch": 6.533333333333333,
+      "grad_norm": 3.8792476654052734,
+      "learning_rate": 2.192592592592593e-05,
+      "loss": 1.6964,
+      "step": 490
+    },
+    {
+      "epoch": 6.533333333333333,
+      "eval_loss": 2.8918919563293457,
+      "eval_runtime": 43.9143,
+      "eval_samples_per_second": 22.772,
+      "eval_steps_per_second": 2.846,
+      "step": 490
+    },
+    {
+      "epoch": 6.666666666666667,
+      "grad_norm": 3.8439388275146484,
+      "learning_rate": 2.074074074074074e-05,
+      "loss": 1.7524,
+      "step": 500
+    },
+    {
+      "epoch": 6.666666666666667,
+      "eval_loss": 2.890720844268799,
+      "eval_runtime": 43.9225,
+      "eval_samples_per_second": 22.767,
+      "eval_steps_per_second": 2.846,
+      "step": 500
+    },
+    {
+      "epoch": 6.8,
+      "grad_norm": 3.7934892177581787,
+      "learning_rate": 1.9555555555555557e-05,
+      "loss": 1.7211,
+      "step": 510
+    },
+    {
+      "epoch": 6.8,
+      "eval_loss": 2.8894593715667725,
+      "eval_runtime": 43.9778,
+      "eval_samples_per_second": 22.739,
+      "eval_steps_per_second": 2.842,
+      "step": 510
+    },
+    {
+      "epoch": 6.933333333333334,
+      "grad_norm": 3.739837884902954,
+      "learning_rate": 1.837037037037037e-05,
+      "loss": 1.6917,
+      "step": 520
+    },
+    {
+      "epoch": 6.933333333333334,
+      "eval_loss": 2.8792428970336914,
+      "eval_runtime": 43.9841,
+      "eval_samples_per_second": 22.735,
+      "eval_steps_per_second": 2.842,
+      "step": 520
+    },
+    {
+      "epoch": 7.066666666666666,
+      "grad_norm": 3.616173267364502,
+      "learning_rate": 1.7185185185185185e-05,
+      "loss": 1.7032,
+      "step": 530
+    },
+    {
+      "epoch": 7.066666666666666,
+      "eval_loss": 2.9059717655181885,
+      "eval_runtime": 43.9541,
+      "eval_samples_per_second": 22.751,
+      "eval_steps_per_second": 2.844,
+      "step": 530
+    },
+    {
+      "epoch": 7.2,
+      "grad_norm": 4.411597728729248,
+      "learning_rate": 1.6000000000000003e-05,
+      "loss": 1.5858,
+      "step": 540
+    },
+    {
+      "epoch": 7.2,
+      "eval_loss": 2.969313859939575,
+      "eval_runtime": 43.9721,
+      "eval_samples_per_second": 22.742,
+      "eval_steps_per_second": 2.843,
+      "step": 540
+    },
+    {
+      "epoch": 7.333333333333333,
+      "grad_norm": 3.8424997329711914,
+      "learning_rate": 1.4814814814814815e-05,
+      "loss": 1.6097,
+      "step": 550
+    },
+    {
+      "epoch": 7.333333333333333,
+      "eval_loss": 2.9442644119262695,
+      "eval_runtime": 43.9947,
+      "eval_samples_per_second": 22.73,
+      "eval_steps_per_second": 2.841,
+      "step": 550
+    },
+    {
+      "epoch": 7.466666666666667,
+      "grad_norm": 5.166232109069824,
+      "learning_rate": 1.362962962962963e-05,
+      "loss": 1.6124,
+      "step": 560
+    },
+    {
+      "epoch": 7.466666666666667,
+      "eval_loss": 2.945424795150757,
+      "eval_runtime": 43.9682,
+      "eval_samples_per_second": 22.744,
+      "eval_steps_per_second": 2.843,
+      "step": 560
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 9.17620031225856e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-570/README.md

@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-570/adapter_config.json

@@ -0,0 +1,31 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/pythia-6_9b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "dense_h_to_4h",
+    "query_key_value",
+    "dense",
+    "dense_4h_to_h"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-570/trainer_state.json

@@ -0,0 +1,888 @@
+{
+  "best_metric": 2.5317564010620117,
+  "best_model_checkpoint": "./output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-150",
+  "epoch": 7.6,
+  "eval_steps": 10,
+  "global_step": 570,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.13333333333333333,
+      "grad_norm": 0.4347652792930603,
+      "learning_rate": 7.881481481481482e-05,
+      "loss": 2.4954,
+      "step": 10
+    },
+    {
+      "epoch": 0.13333333333333333,
+      "eval_loss": 2.556234359741211,
+      "eval_runtime": 43.818,
+      "eval_samples_per_second": 22.822,
+      "eval_steps_per_second": 2.853,
+      "step": 10
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "grad_norm": 0.40230727195739746,
+      "learning_rate": 7.762962962962963e-05,
+      "loss": 2.5574,
+      "step": 20
+    },
+    {
+      "epoch": 0.26666666666666666,
+      "eval_loss": 2.552377462387085,
+      "eval_runtime": 43.8488,
+      "eval_samples_per_second": 22.806,
+      "eval_steps_per_second": 2.851,
+      "step": 20
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.3980488181114197,
+      "learning_rate": 7.644444444444445e-05,
+      "loss": 2.4669,
+      "step": 30
+    },
+    {
+      "epoch": 0.4,
+      "eval_loss": 2.549164056777954,
+      "eval_runtime": 43.8389,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 30
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "grad_norm": 0.4006142020225525,
+      "learning_rate": 7.525925925925926e-05,
+      "loss": 2.5199,
+      "step": 40
+    },
+    {
+      "epoch": 0.5333333333333333,
+      "eval_loss": 2.546046495437622,
+      "eval_runtime": 43.8456,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 40
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 0.4202616512775421,
+      "learning_rate": 7.407407407407409e-05,
+      "loss": 2.5619,
+      "step": 50
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "eval_loss": 2.5431504249572754,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 50
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.3871513307094574,
+      "learning_rate": 7.28888888888889e-05,
+      "loss": 2.5057,
+      "step": 60
+    },
+    {
+      "epoch": 0.8,
+      "eval_loss": 2.5413730144500732,
+      "eval_runtime": 43.8646,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 60
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "grad_norm": 0.36390039324760437,
+      "learning_rate": 7.170370370370371e-05,
+      "loss": 2.4606,
+      "step": 70
+    },
+    {
+      "epoch": 0.9333333333333333,
+      "eval_loss": 2.5389301776885986,
+      "eval_runtime": 43.8837,
+      "eval_samples_per_second": 22.788,
+      "eval_steps_per_second": 2.848,
+      "step": 70
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "grad_norm": 0.4081075191497803,
+      "learning_rate": 7.051851851851853e-05,
+      "loss": 2.4696,
+      "step": 80
+    },
+    {
+      "epoch": 1.0666666666666667,
+      "eval_loss": 2.5368435382843018,
+      "eval_runtime": 43.8696,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 80
+    },
+    {
+      "epoch": 1.2,
+      "grad_norm": 0.5448070764541626,
+      "learning_rate": 6.933333333333334e-05,
+      "loss": 2.4258,
+      "step": 90
+    },
+    {
+      "epoch": 1.2,
+      "eval_loss": 2.538212776184082,
+      "eval_runtime": 43.8585,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 90
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 0.7155500650405884,
+      "learning_rate": 6.814814814814815e-05,
+      "loss": 2.4865,
+      "step": 100
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "eval_loss": 2.540060043334961,
+      "eval_runtime": 43.8337,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 100
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "grad_norm": 0.7326843738555908,
+      "learning_rate": 6.696296296296296e-05,
+      "loss": 2.4391,
+      "step": 110
+    },
+    {
+      "epoch": 1.4666666666666668,
+      "eval_loss": 2.5385019779205322,
+      "eval_runtime": 43.8789,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 110
+    },
+    {
+      "epoch": 1.6,
+      "grad_norm": 0.8026068806648254,
+      "learning_rate": 6.577777777777777e-05,
+      "loss": 2.4001,
+      "step": 120
+    },
+    {
+      "epoch": 1.6,
+      "eval_loss": 2.5356342792510986,
+      "eval_runtime": 43.8699,
+      "eval_samples_per_second": 22.795,
+      "eval_steps_per_second": 2.849,
+      "step": 120
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "grad_norm": 0.8492558598518372,
+      "learning_rate": 6.45925925925926e-05,
+      "loss": 2.387,
+      "step": 130
+    },
+    {
+      "epoch": 1.7333333333333334,
+      "eval_loss": 2.5329699516296387,
+      "eval_runtime": 43.8654,
+      "eval_samples_per_second": 22.797,
+      "eval_steps_per_second": 2.85,
+      "step": 130
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "grad_norm": 1.1200364828109741,
+      "learning_rate": 6.340740740740741e-05,
+      "loss": 2.3817,
+      "step": 140
+    },
+    {
+      "epoch": 1.8666666666666667,
+      "eval_loss": 2.5319204330444336,
+      "eval_runtime": 43.847,
+      "eval_samples_per_second": 22.807,
+      "eval_steps_per_second": 2.851,
+      "step": 140
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.9766451120376587,
+      "learning_rate": 6.222222222222223e-05,
+      "loss": 2.4193,
+      "step": 150
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 2.5317564010620117,
+      "eval_runtime": 43.8504,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 150
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "grad_norm": 1.0703226327896118,
+      "learning_rate": 6.103703703703704e-05,
+      "loss": 2.3341,
+      "step": 160
+    },
+    {
+      "epoch": 2.1333333333333333,
+      "eval_loss": 2.5564167499542236,
+      "eval_runtime": 43.8299,
+      "eval_samples_per_second": 22.815,
+      "eval_steps_per_second": 2.852,
+      "step": 160
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "grad_norm": 1.3115178346633911,
+      "learning_rate": 5.9851851851851855e-05,
+      "loss": 2.2182,
+      "step": 170
+    },
+    {
+      "epoch": 2.2666666666666666,
+      "eval_loss": 2.5810468196868896,
+      "eval_runtime": 43.8366,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 170
+    },
+    {
+      "epoch": 2.4,
+      "grad_norm": 1.4998687505722046,
+      "learning_rate": 5.8666666666666665e-05,
+      "loss": 2.2379,
+      "step": 180
+    },
+    {
+      "epoch": 2.4,
+      "eval_loss": 2.580641269683838,
+      "eval_runtime": 43.8362,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.852,
+      "step": 180
+    },
+    {
+      "epoch": 2.533333333333333,
+      "grad_norm": 1.6269217729568481,
+      "learning_rate": 5.748148148148149e-05,
+      "loss": 2.2346,
+      "step": 190
+    },
+    {
+      "epoch": 2.533333333333333,
+      "eval_loss": 2.572070360183716,
+      "eval_runtime": 43.8376,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 190
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 1.5595163106918335,
+      "learning_rate": 5.62962962962963e-05,
+      "loss": 2.225,
+      "step": 200
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "eval_loss": 2.574326276779175,
+      "eval_runtime": 43.8537,
+      "eval_samples_per_second": 22.803,
+      "eval_steps_per_second": 2.85,
+      "step": 200
+    },
+    {
+      "epoch": 2.8,
+      "grad_norm": 1.673547387123108,
+      "learning_rate": 5.511111111111112e-05,
+      "loss": 2.2471,
+      "step": 210
+    },
+    {
+      "epoch": 2.8,
+      "eval_loss": 2.5765159130096436,
+      "eval_runtime": 43.8369,
+      "eval_samples_per_second": 22.812,
+      "eval_steps_per_second": 2.851,
+      "step": 210
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "grad_norm": 1.5295490026474,
+      "learning_rate": 5.392592592592593e-05,
+      "loss": 2.204,
+      "step": 220
+    },
+    {
+      "epoch": 2.9333333333333336,
+      "eval_loss": 2.5766921043395996,
+      "eval_runtime": 43.8443,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 220
+    },
+    {
+      "epoch": 3.066666666666667,
+      "grad_norm": 1.6709380149841309,
+      "learning_rate": 5.274074074074074e-05,
+      "loss": 2.1753,
+      "step": 230
+    },
+    {
+      "epoch": 3.066666666666667,
+      "eval_loss": 2.602360248565674,
+      "eval_runtime": 43.8576,
+      "eval_samples_per_second": 22.801,
+      "eval_steps_per_second": 2.85,
+      "step": 230
+    },
+    {
+      "epoch": 3.2,
+      "grad_norm": 2.053478240966797,
+      "learning_rate": 5.155555555555556e-05,
+      "loss": 2.0405,
+      "step": 240
+    },
+    {
+      "epoch": 3.2,
+      "eval_loss": 2.6636874675750732,
+      "eval_runtime": 43.8509,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 240
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "grad_norm": 1.8616771697998047,
+      "learning_rate": 5.037037037037037e-05,
+      "loss": 2.0265,
+      "step": 250
+    },
+    {
+      "epoch": 3.3333333333333335,
+      "eval_loss": 2.6536307334899902,
+      "eval_runtime": 43.8433,
+      "eval_samples_per_second": 22.808,
+      "eval_steps_per_second": 2.851,
+      "step": 250
+    },
+    {
+      "epoch": 3.466666666666667,
+      "grad_norm": 2.1498146057128906,
+      "learning_rate": 4.918518518518519e-05,
+      "loss": 2.1386,
+      "step": 260
+    },
+    {
+      "epoch": 3.466666666666667,
+      "eval_loss": 2.658257246017456,
+      "eval_runtime": 43.8516,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.851,
+      "step": 260
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 2.203857660293579,
+      "learning_rate": 4.8e-05,
+      "loss": 2.0367,
+      "step": 270
+    },
+    {
+      "epoch": 3.6,
+      "eval_loss": 2.658139228820801,
+      "eval_runtime": 43.8709,
+      "eval_samples_per_second": 22.794,
+      "eval_steps_per_second": 2.849,
+      "step": 270
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "grad_norm": 2.0805578231811523,
+      "learning_rate": 4.681481481481481e-05,
+      "loss": 2.0226,
+      "step": 280
+    },
+    {
+      "epoch": 3.7333333333333334,
+      "eval_loss": 2.646563768386841,
+      "eval_runtime": 43.8726,
+      "eval_samples_per_second": 22.793,
+      "eval_steps_per_second": 2.849,
+      "step": 280
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "grad_norm": 2.27193546295166,
+      "learning_rate": 4.5629629629629636e-05,
+      "loss": 2.1099,
+      "step": 290
+    },
+    {
+      "epoch": 3.8666666666666667,
+      "eval_loss": 2.6486735343933105,
+      "eval_runtime": 43.881,
+      "eval_samples_per_second": 22.789,
+      "eval_steps_per_second": 2.849,
+      "step": 290
+    },
+    {
+      "epoch": 4.0,
+      "grad_norm": 2.0627055168151855,
+      "learning_rate": 4.444444444444445e-05,
+      "loss": 2.0996,
+      "step": 300
+    },
+    {
+      "epoch": 4.0,
+      "eval_loss": 2.644541025161743,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 300
+    },
+    {
+      "epoch": 4.133333333333334,
+      "grad_norm": 2.6526894569396973,
+      "learning_rate": 4.3259259259259264e-05,
+      "loss": 1.8896,
+      "step": 310
+    },
+    {
+      "epoch": 4.133333333333334,
+      "eval_loss": 2.7607998847961426,
+      "eval_runtime": 43.8953,
+      "eval_samples_per_second": 22.781,
+      "eval_steps_per_second": 2.848,
+      "step": 310
+    },
+    {
+      "epoch": 4.266666666666667,
+      "grad_norm": 2.813822031021118,
+      "learning_rate": 4.2074074074074075e-05,
+      "loss": 1.8568,
+      "step": 320
+    },
+    {
+      "epoch": 4.266666666666667,
+      "eval_loss": 2.7357044219970703,
+      "eval_runtime": 43.8795,
+      "eval_samples_per_second": 22.79,
+      "eval_steps_per_second": 2.849,
+      "step": 320
+    },
+    {
+      "epoch": 4.4,
+      "grad_norm": 3.134248733520508,
+      "learning_rate": 4.088888888888889e-05,
+      "loss": 1.9636,
+      "step": 330
+    },
+    {
+      "epoch": 4.4,
+      "eval_loss": 2.742431640625,
+      "eval_runtime": 43.8639,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 330
+    },
+    {
+      "epoch": 4.533333333333333,
+      "grad_norm": 2.727226495742798,
+      "learning_rate": 3.970370370370371e-05,
+      "loss": 1.9148,
+      "step": 340
+    },
+    {
+      "epoch": 4.533333333333333,
+      "eval_loss": 2.7314682006835938,
+      "eval_runtime": 43.852,
+      "eval_samples_per_second": 22.804,
+      "eval_steps_per_second": 2.85,
+      "step": 340
+    },
+    {
+      "epoch": 4.666666666666667,
+      "grad_norm": 2.768984079360962,
+      "learning_rate": 3.851851851851852e-05,
+      "loss": 1.9134,
+      "step": 350
+    },
+    {
+      "epoch": 4.666666666666667,
+      "eval_loss": 2.7299180030822754,
+      "eval_runtime": 43.8498,
+      "eval_samples_per_second": 22.805,
+      "eval_steps_per_second": 2.851,
+      "step": 350
+    },
+    {
+      "epoch": 4.8,
+      "grad_norm": 3.0203487873077393,
+      "learning_rate": 3.733333333333334e-05,
+      "loss": 1.9445,
+      "step": 360
+    },
+    {
+      "epoch": 4.8,
+      "eval_loss": 2.7333309650421143,
+      "eval_runtime": 43.8634,
+      "eval_samples_per_second": 22.798,
+      "eval_steps_per_second": 2.85,
+      "step": 360
+    },
+    {
+      "epoch": 4.933333333333334,
+      "grad_norm": 2.721759080886841,
+      "learning_rate": 3.614814814814815e-05,
+      "loss": 1.9199,
+      "step": 370
+    },
+    {
+      "epoch": 4.933333333333334,
+      "eval_loss": 2.7230074405670166,
+      "eval_runtime": 43.8351,
+      "eval_samples_per_second": 22.813,
+      "eval_steps_per_second": 2.852,
+      "step": 370
+    },
+    {
+      "epoch": 5.066666666666666,
+      "grad_norm": 2.812037467956543,
+      "learning_rate": 3.4962962962962965e-05,
+      "loss": 1.9396,
+      "step": 380
+    },
+    {
+      "epoch": 5.066666666666666,
+      "eval_loss": 2.7738075256347656,
+      "eval_runtime": 43.8405,
+      "eval_samples_per_second": 22.81,
+      "eval_steps_per_second": 2.851,
+      "step": 380
+    },
+    {
+      "epoch": 5.2,
+      "grad_norm": 3.347679376602173,
+      "learning_rate": 3.377777777777778e-05,
+      "loss": 1.8374,
+      "step": 390
+    },
+    {
+      "epoch": 5.2,
+      "eval_loss": 2.830467700958252,
+      "eval_runtime": 43.8379,
+      "eval_samples_per_second": 22.811,
+      "eval_steps_per_second": 2.851,
+      "step": 390
+    },
+    {
+      "epoch": 5.333333333333333,
+      "grad_norm": 3.1343460083007812,
+      "learning_rate": 3.259259259259259e-05,
+      "loss": 1.7472,
+      "step": 400
+    },
+    {
+      "epoch": 5.333333333333333,
+      "eval_loss": 2.8105757236480713,
+      "eval_runtime": 43.9522,
+      "eval_samples_per_second": 22.752,
+      "eval_steps_per_second": 2.844,
+      "step": 400
+    },
+    {
+      "epoch": 5.466666666666667,
+      "grad_norm": 3.431727170944214,
+      "learning_rate": 3.140740740740741e-05,
+      "loss": 1.8274,
+      "step": 410
+    },
+    {
+      "epoch": 5.466666666666667,
+      "eval_loss": 2.816023826599121,
+      "eval_runtime": 43.9615,
+      "eval_samples_per_second": 22.747,
+      "eval_steps_per_second": 2.843,
+      "step": 410
+    },
+    {
+      "epoch": 5.6,
+      "grad_norm": 3.4572854042053223,
+      "learning_rate": 3.0222222222222225e-05,
+      "loss": 1.8135,
+      "step": 420
+    },
+    {
+      "epoch": 5.6,
+      "eval_loss": 2.817023992538452,
+      "eval_runtime": 43.9443,
+      "eval_samples_per_second": 22.756,
+      "eval_steps_per_second": 2.845,
+      "step": 420
+    },
+    {
+      "epoch": 5.733333333333333,
+      "grad_norm": 3.286614179611206,
+      "learning_rate": 2.9037037037037042e-05,
+      "loss": 1.8312,
+      "step": 430
+    },
+    {
+      "epoch": 5.733333333333333,
+      "eval_loss": 2.813601493835449,
+      "eval_runtime": 43.9055,
+      "eval_samples_per_second": 22.776,
+      "eval_steps_per_second": 2.847,
+      "step": 430
+    },
+    {
+      "epoch": 5.866666666666667,
+      "grad_norm": 3.152069568634033,
+      "learning_rate": 2.7851851851851856e-05,
+      "loss": 1.7372,
+      "step": 440
+    },
+    {
+      "epoch": 5.866666666666667,
+      "eval_loss": 2.8068931102752686,
+      "eval_runtime": 43.9514,
+      "eval_samples_per_second": 22.752,
+      "eval_steps_per_second": 2.844,
+      "step": 440
+    },
+    {
+      "epoch": 6.0,
+      "grad_norm": 3.1378376483917236,
+      "learning_rate": 2.6666666666666667e-05,
+      "loss": 1.7966,
+      "step": 450
+    },
+    {
+      "epoch": 6.0,
+      "eval_loss": 2.8000402450561523,
+      "eval_runtime": 43.9182,
+      "eval_samples_per_second": 22.77,
+      "eval_steps_per_second": 2.846,
+      "step": 450
+    },
+    {
+      "epoch": 6.133333333333334,
+      "grad_norm": 3.289393424987793,
+      "learning_rate": 2.5481481481481484e-05,
+      "loss": 1.7021,
+      "step": 460
+    },
+    {
+      "epoch": 6.133333333333334,
+      "eval_loss": 2.8974051475524902,
+      "eval_runtime": 43.8673,
+      "eval_samples_per_second": 22.796,
+      "eval_steps_per_second": 2.85,
+      "step": 460
+    },
+    {
+      "epoch": 6.266666666666667,
+      "grad_norm": 3.662322998046875,
+      "learning_rate": 2.4296296296296298e-05,
+      "loss": 1.6801,
+      "step": 470
+    },
+    {
+      "epoch": 6.266666666666667,
+      "eval_loss": 2.891542911529541,
+      "eval_runtime": 43.9675,
+      "eval_samples_per_second": 22.744,
+      "eval_steps_per_second": 2.843,
+      "step": 470
+    },
+    {
+      "epoch": 6.4,
+      "grad_norm": 3.6940433979034424,
+      "learning_rate": 2.3111111111111112e-05,
+      "loss": 1.6549,
+      "step": 480
+    },
+    {
+      "epoch": 6.4,
+      "eval_loss": 2.884908676147461,
+      "eval_runtime": 43.9337,
+      "eval_samples_per_second": 22.762,
+      "eval_steps_per_second": 2.845,
+      "step": 480
+    },
+    {
+      "epoch": 6.533333333333333,
+      "grad_norm": 3.8792476654052734,
+      "learning_rate": 2.192592592592593e-05,
+      "loss": 1.6964,
+      "step": 490
+    },
+    {
+      "epoch": 6.533333333333333,
+      "eval_loss": 2.8918919563293457,
+      "eval_runtime": 43.9143,
+      "eval_samples_per_second": 22.772,
+      "eval_steps_per_second": 2.846,
+      "step": 490
+    },
+    {
+      "epoch": 6.666666666666667,
+      "grad_norm": 3.8439388275146484,
+      "learning_rate": 2.074074074074074e-05,
+      "loss": 1.7524,
+      "step": 500
+    },
+    {
+      "epoch": 6.666666666666667,
+      "eval_loss": 2.890720844268799,
+      "eval_runtime": 43.9225,
+      "eval_samples_per_second": 22.767,
+      "eval_steps_per_second": 2.846,
+      "step": 500
+    },
+    {
+      "epoch": 6.8,
+      "grad_norm": 3.7934892177581787,
+      "learning_rate": 1.9555555555555557e-05,
+      "loss": 1.7211,
+      "step": 510
+    },
+    {
+      "epoch": 6.8,
+      "eval_loss": 2.8894593715667725,
+      "eval_runtime": 43.9778,
+      "eval_samples_per_second": 22.739,
+      "eval_steps_per_second": 2.842,
+      "step": 510
+    },
+    {
+      "epoch": 6.933333333333334,
+      "grad_norm": 3.739837884902954,
+      "learning_rate": 1.837037037037037e-05,
+      "loss": 1.6917,
+      "step": 520
+    },
+    {
+      "epoch": 6.933333333333334,
+      "eval_loss": 2.8792428970336914,
+      "eval_runtime": 43.9841,
+      "eval_samples_per_second": 22.735,
+      "eval_steps_per_second": 2.842,
+      "step": 520
+    },
+    {
+      "epoch": 7.066666666666666,
+      "grad_norm": 3.616173267364502,
+      "learning_rate": 1.7185185185185185e-05,
+      "loss": 1.7032,
+      "step": 530
+    },
+    {
+      "epoch": 7.066666666666666,
+      "eval_loss": 2.9059717655181885,
+      "eval_runtime": 43.9541,
+      "eval_samples_per_second": 22.751,
+      "eval_steps_per_second": 2.844,
+      "step": 530
+    },
+    {
+      "epoch": 7.2,
+      "grad_norm": 4.411597728729248,
+      "learning_rate": 1.6000000000000003e-05,
+      "loss": 1.5858,
+      "step": 540
+    },
+    {
+      "epoch": 7.2,
+      "eval_loss": 2.969313859939575,
+      "eval_runtime": 43.9721,
+      "eval_samples_per_second": 22.742,
+      "eval_steps_per_second": 2.843,
+      "step": 540
+    },
+    {
+      "epoch": 7.333333333333333,
+      "grad_norm": 3.8424997329711914,
+      "learning_rate": 1.4814814814814815e-05,
+      "loss": 1.6097,
+      "step": 550
+    },
+    {
+      "epoch": 7.333333333333333,
+      "eval_loss": 2.9442644119262695,
+      "eval_runtime": 43.9947,
+      "eval_samples_per_second": 22.73,
+      "eval_steps_per_second": 2.841,
+      "step": 550
+    },
+    {
+      "epoch": 7.466666666666667,
+      "grad_norm": 5.166232109069824,
+      "learning_rate": 1.362962962962963e-05,
+      "loss": 1.6124,
+      "step": 560
+    },
+    {
+      "epoch": 7.466666666666667,
+      "eval_loss": 2.945424795150757,
+      "eval_runtime": 43.9682,
+      "eval_samples_per_second": 22.744,
+      "eval_steps_per_second": 2.843,
+      "step": 560
+    },
+    {
+      "epoch": 7.6,
+      "grad_norm": 4.192744731903076,
+      "learning_rate": 1.2444444444444446e-05,
+      "loss": 1.6204,
+      "step": 570
+    },
+    {
+      "epoch": 7.6,
+      "eval_loss": 2.9401402473449707,
+      "eval_runtime": 43.9497,
+      "eval_samples_per_second": 22.753,
+      "eval_steps_per_second": 2.844,
+      "step": 570
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 675,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 9,
+  "save_steps": 10,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 9.34006103212032e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}

output_ft_more_layers_bookcorpus2_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-bookcorpus2-8e-05/checkpoint-580/README.md

@@ -0,0 +1,202 @@
+---
+base_model: /workspace/pythia-6_9b
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2