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README.md

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+---
+license: other
+base_model: meta-llama/Meta-Llama-3-8B
+tags:
+- llama-factory
+- full
+- generated_from_trainer
+model-index:
+- name: C014_llama3-8b-base_pretrain_20240428_005832
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# C014_llama3-8b-base_pretrain_20240428_005832
+
+This model is a fine-tuned version of [/mnt/models-pku/progressalign/shared_storage/downloaded_models/llama3-8b-base](https://huggingface.co//mnt/models-pku/progressalign/shared_storage/downloaded_models/llama3-8b-base) on the C014_data dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.2045
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 1.5e-05
+- train_batch_size: 8
+- eval_batch_size: 16
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- total_train_batch_size: 64
+- total_eval_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: polynomial
+- lr_scheduler_warmup_steps: 20
+- num_epochs: 4.0
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 2.5789        | 0.0152 | 1    | 2.6458          |
+| 2.5672        | 0.0758 | 5    | 2.6280          |
+| 2.5751        | 0.1515 | 10   | 2.5314          |
+| 2.418         | 0.2273 | 15   | 2.4634          |
+| 2.4701        | 0.3030 | 20   | 2.4177          |
+| 2.3904        | 0.3788 | 25   | 2.3785          |
+| 2.3539        | 0.4545 | 30   | 2.3378          |
+| 2.3101        | 0.5303 | 35   | 2.3082          |
+| 2.3254        | 0.6061 | 40   | 2.2816          |
+| 2.2762        | 0.6818 | 45   | 2.2614          |
+| 2.2525        | 0.7576 | 50   | 2.2458          |
+| 2.2777        | 0.8333 | 55   | 2.2321          |
+| 2.2054        | 0.9091 | 60   | 2.2206          |
+| 2.237         | 0.9848 | 65   | 2.2113          |
+| 1.986         | 1.0606 | 70   | 2.2115          |
+| 1.9373        | 1.1364 | 75   | 2.2217          |
+| 1.9228        | 1.2121 | 80   | 2.2132          |
+| 1.9084        | 1.2879 | 85   | 2.2118          |
+| 1.9684        | 1.3636 | 90   | 2.2122          |
+| 1.9126        | 1.4394 | 95   | 2.2094          |
+| 1.9101        | 1.5152 | 100  | 2.2066          |
+| 1.8496        | 1.5909 | 105  | 2.2058          |
+| 1.9154        | 1.6667 | 110  | 2.2057          |
+| 1.9233        | 1.7424 | 115  | 2.2056          |
+| 1.9198        | 1.8182 | 120  | 2.2052          |
+| 1.9229        | 1.8939 | 125  | 2.2048          |
+| 1.8913        | 1.9697 | 130  | 2.2045          |
+| 1.8814        | 2.0455 | 135  | 2.2046          |
+| 1.8813        | 2.1212 | 140  | 2.2051          |
+| 1.8912        | 2.1970 | 145  | 2.2058          |
+| 1.9184        | 2.2727 | 150  | 2.2065          |
+| 1.8662        | 2.3485 | 155  | 2.2071          |
+| 1.8809        | 2.4242 | 160  | 2.2074          |
+| 1.8591        | 2.5    | 165  | 2.2077          |
+| 1.8731        | 2.5758 | 170  | 2.2079          |
+| 1.8948        | 2.6515 | 175  | 2.2082          |
+| 1.8876        | 2.7273 | 180  | 2.2082          |
+| 1.8408        | 2.8030 | 185  | 2.2083          |
+| 1.8931        | 2.8788 | 190  | 2.2082          |
+| 1.8569        | 2.9545 | 195  | 2.2080          |
+| 1.8621        | 3.0303 | 200  | 2.2079          |
+| 1.8863        | 3.1061 | 205  | 2.2078          |
+| 1.9021        | 3.1818 | 210  | 2.2079          |
+| 1.8648        | 3.2576 | 215  | 2.2080          |
+| 1.8443        | 3.3333 | 220  | 2.2081          |
+| 1.8978        | 3.4091 | 225  | 2.2080          |
+| 1.8658        | 3.4848 | 230  | 2.2080          |
+| 1.8706        | 3.5606 | 235  | 2.2079          |
+| 1.8855        | 3.6364 | 240  | 2.2078          |
+| 1.8535        | 3.7121 | 245  | 2.2078          |
+| 1.9062        | 3.7879 | 250  | 2.2079          |
+| 1.8628        | 3.8636 | 255  | 2.2078          |
+| 1.8484        | 3.9394 | 260  | 2.2077          |
+
+
+### Framework versions
+
+- Transformers 4.40.0
+- Pytorch 2.1.2+cu121
+- Datasets 2.18.0
+- Tokenizers 0.19.1

all_results.json

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+{
+    "epoch": 4.0,
+    "eval_loss": 2.204540491104126,
+    "eval_runtime": 6.002,
+    "eval_samples_per_second": 77.474,
+    "eval_steps_per_second": 0.666,
+    "perplexity": 9.066084664011177,
+    "total_flos": 27428734894080.0,
+    "train_loss": 2.005241002097274,
+    "train_runtime": 8788.5675,
+    "train_samples_per_second": 1.904,
+    "train_steps_per_second": 0.03
+}

config.json

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+{
+  "_name_or_path": "/mnt/models-pku/progressalign/shared_storage/downloaded_models/llama3-8b-base",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "eos_token_id": 128001,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 8192,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 500000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.40.0",
+  "use_cache": false,
+  "vocab_size": 128256
+}

eval_results.json

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+{
+    "epoch": 4.0,
+    "eval_loss": 2.204540491104126,
+    "eval_runtime": 6.002,
+    "eval_samples_per_second": 77.474,
+    "eval_steps_per_second": 0.666,
+    "perplexity": 9.066084664011177
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 128000,
+  "eos_token_id": 128001,
+  "transformers_version": "4.40.0"
+}

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special_tokens_map.json

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tokenizer_config.json

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train_results.json

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+}

trainer_log.jsonl

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