diff --git "a/log.txt" "b/log.txt"
new file mode 100644--- /dev/null
+++ "b/log.txt"
@@ -0,0 +1,6888 @@
+The following values were not passed to `accelerate launch` and had defaults used instead:
+	`--num_processes` was set to a value of `4`
+		More than one GPU was found, enabling multi-GPU training.
+		If this was unintended please pass in `--num_processes=1`.
+	`--num_machines` was set to a value of `1`
+	`--mixed_precision` was set to a value of `'no'`
+	`--dynamo_backend` was set to a value of `'no'`
+To avoid this warning pass in values for each of the problematic parameters or run `accelerate config`.
+Params using prompt template alpaca:
+base_model: baichuan-inc/Baichuan2-7B-Base
+data_path: ../../data/belle_dolphine/p12.jsonl
+output_dir: ../out/lora/p12
+batch_size: 32
+micro_batch_size: 2
+num_epochs: 1
+learning_rate: 0.0004
+cutoff_len: 4096
+val_set_size: 0
+lr_scheduler: cosine
+warmup_steps: 100
+lora_r: 16
+lora_alpha: 16
+lora_dropout: 0.05
+lora_target_modules: ['gate_proj', 'down_proj', 'up_proj']
+train_on_inputs: False
+add_eos_token: False
+group_by_length: False
+wandb_project: lora-moe
+wandb_run_name: belle_dolphine-p12
+wandb_watch: 
+wandb_log_model: 
+resume_from_checkpoint: False
+
+gradient_accumulation_steps:  4
+gradient_accumulation_steps:  4
+gradient_accumulation_steps:  4
+gradient_accumulation_steps:  4
+
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+
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+pre-trained model's BOS EOS and PAD token id: 1 2 0  => It should be 1 2 None
+pre-trained model's BOS EOS and PAD token id: 1 2 0  => It should be 1 2 None
+
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+pre-trained model's BOS EOS and PAD token id: 1 2 0  => It should be 1 2 None
+pre-trained model's BOS EOS and PAD token id: 1 2 0  => It should be 1 2 None
+trainable params: 23,199,744 || all params: 7,529,172,992 || trainable%: 0.30813137146205183
+trainable params: 23,199,744 || all params: 7,529,172,992 || trainable%: 0.30813137146205183
+
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+trainable params: 23,199,744 || all params: 7,529,172,992 || trainable%: 0.30813137146205183
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+/home/aiops/duanky/miniconda3/envs/lora/lib/python3.11/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
+  warnings.warn(
+/home/aiops/duanky/miniconda3/envs/lora/lib/python3.11/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
+  warnings.warn(
+/home/aiops/duanky/miniconda3/envs/lora/lib/python3.11/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
+  warnings.warn(
+wandb: Currently logged in as: k-duan (nus_keyu). Use `wandb login --relogin` to force relogin
+wandb: Tracking run with wandb version 0.16.1
+wandb: Run data is saved locally in /home/aiops/duanky/lora-moe/experiments/launch_scripts/wandb/run-20231229_074425-39wnh4vr
+wandb: Run `wandb offline` to turn off syncing.
+wandb: Syncing run belle_dolphine-p12
+wandb: ⭐️ View project at https://wandb.ai/nus_keyu/lora-moe
+wandb: 🚀 View run at https://wandb.ai/nus_keyu/lora-moe/runs/39wnh4vr
+
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+  warnings.warn(
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{'loss': 1.9717, 'learning_rate': 6.800000000000001e-05, 'epoch': 0.0}
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{'loss': 1.8316, 'learning_rate': 7.2e-05, 'epoch': 0.0}
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{'loss': 1.8734, 'learning_rate': 7.6e-05, 'epoch': 0.0}
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{'loss': 1.7933, 'learning_rate': 8e-05, 'epoch': 0.0}
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{'loss': 2.0163, 'learning_rate': 8.4e-05, 'epoch': 0.0}
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{'loss': 1.9915, 'learning_rate': 8.800000000000001e-05, 'epoch': 0.0}
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{'loss': 1.8712, 'learning_rate': 9.200000000000001e-05, 'epoch': 0.0}
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{'loss': 1.7655, 'learning_rate': 9.6e-05, 'epoch': 0.0}
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{'loss': 1.91, 'learning_rate': 0.0001, 'epoch': 0.0}
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{'loss': 2.0138, 'learning_rate': 0.00010400000000000001, 'epoch': 0.0}
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{'loss': 1.8081, 'learning_rate': 0.00010800000000000001, 'epoch': 0.0}
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{'loss': 1.8079, 'learning_rate': 0.00011200000000000001, 'epoch': 0.0}
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{'loss': 1.882, 'learning_rate': 0.000116, 'epoch': 0.0}
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{'loss': 2.0069, 'learning_rate': 0.00012, 'epoch': 0.0}
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{'loss': 1.8437, 'learning_rate': 0.000124, 'epoch': 0.0}
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{'loss': 1.852, 'learning_rate': 0.00012800000000000002, 'epoch': 0.0}
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{'loss': 1.7443, 'learning_rate': 0.000132, 'epoch': 0.0}
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{'loss': 1.7793, 'learning_rate': 0.00013600000000000003, 'epoch': 0.01}
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{'loss': 1.9135, 'learning_rate': 0.00014, 'epoch': 0.01}
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{'loss': 1.8929, 'learning_rate': 0.000144, 'epoch': 0.01}
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{'loss': 1.9677, 'learning_rate': 0.000148, 'epoch': 0.01}
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{'loss': 2.056, 'learning_rate': 0.000152, 'epoch': 0.01}
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{'loss': 1.7649, 'learning_rate': 0.00015600000000000002, 'epoch': 0.01}
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{'loss': 1.89, 'learning_rate': 0.00016, 'epoch': 0.01}
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{'loss': 1.8011, 'learning_rate': 0.000164, 'epoch': 0.01}
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{'loss': 1.9124, 'learning_rate': 0.000168, 'epoch': 0.01}
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{'loss': 1.9942, 'learning_rate': 0.000172, 'epoch': 0.01}
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{'loss': 1.971, 'learning_rate': 0.00017600000000000002, 'epoch': 0.01}
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{'loss': 1.915, 'learning_rate': 0.00018, 'epoch': 0.01}
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{'loss': 1.8294, 'learning_rate': 0.00018400000000000003, 'epoch': 0.01}
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{'loss': 1.8736, 'learning_rate': 0.000188, 'epoch': 0.01}
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{'loss': 1.7379, 'learning_rate': 0.000192, 'epoch': 0.01}
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{'loss': 1.9866, 'learning_rate': 0.000196, 'epoch': 0.01}
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{'loss': 1.9119, 'learning_rate': 0.0002, 'epoch': 0.01}
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{'loss': 1.9222, 'learning_rate': 0.00020400000000000003, 'epoch': 0.01}
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{'loss': 1.6958, 'learning_rate': 0.00020800000000000001, 'epoch': 0.01}
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{'loss': 2.1636, 'learning_rate': 0.00021200000000000003, 'epoch': 0.01}
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{'loss': 1.928, 'learning_rate': 0.00021600000000000002, 'epoch': 0.01}
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{'loss': 1.8135, 'learning_rate': 0.00022000000000000003, 'epoch': 0.01}
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{'loss': 1.857, 'learning_rate': 0.00022400000000000002, 'epoch': 0.01}
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{'loss': 1.948, 'learning_rate': 0.00022799999999999999, 'epoch': 0.01}
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{'loss': 1.7749, 'learning_rate': 0.000232, 'epoch': 0.01}
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{'loss': 1.8576, 'learning_rate': 0.000236, 'epoch': 0.01}
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{'loss': 1.8794, 'learning_rate': 0.00024, 'epoch': 0.01}
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{'loss': 1.6526, 'learning_rate': 0.000244, 'epoch': 0.01}
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{'loss': 1.7652, 'learning_rate': 0.000248, 'epoch': 0.01}
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{'loss': 1.7747, 'learning_rate': 0.000252, 'epoch': 0.01}
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{'loss': 1.872, 'learning_rate': 0.00025600000000000004, 'epoch': 0.01}
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{'loss': 1.957, 'learning_rate': 0.00026000000000000003, 'epoch': 0.01}
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{'loss': 1.9778, 'learning_rate': 0.000264, 'epoch': 0.01}
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{'loss': 1.6753, 'learning_rate': 0.000268, 'epoch': 0.01}
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{'loss': 1.7244, 'learning_rate': 0.00027200000000000005, 'epoch': 0.01}
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{'loss': 1.917, 'learning_rate': 0.000276, 'epoch': 0.01}
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{'loss': 1.9036, 'learning_rate': 0.00028, 'epoch': 0.01}
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{'loss': 1.7857, 'learning_rate': 0.000284, 'epoch': 0.01}
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{'loss': 1.6636, 'learning_rate': 0.000288, 'epoch': 0.01}
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{'loss': 1.8924, 'learning_rate': 0.000292, 'epoch': 0.01}
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{'loss': 1.92, 'learning_rate': 0.000296, 'epoch': 0.01}
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{'loss': 1.8787, 'learning_rate': 0.00030000000000000003, 'epoch': 0.01}
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{'loss': 1.774, 'learning_rate': 0.000304, 'epoch': 0.01}
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{'loss': 1.8049, 'learning_rate': 0.000308, 'epoch': 0.01}
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{'loss': 1.9016, 'learning_rate': 0.00031200000000000005, 'epoch': 0.01}
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{'loss': 1.7271, 'learning_rate': 0.00031600000000000004, 'epoch': 0.01}
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{'loss': 1.7394, 'learning_rate': 0.00032, 'epoch': 0.01}
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{'loss': 1.9497, 'learning_rate': 0.000324, 'epoch': 0.01}
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{'loss': 1.7302, 'learning_rate': 0.000328, 'epoch': 0.01}
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{'loss': 1.846, 'learning_rate': 0.000332, 'epoch': 0.01}
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{'loss': 1.7626, 'learning_rate': 0.000336, 'epoch': 0.01}
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{'loss': 1.9597, 'learning_rate': 0.00034, 'epoch': 0.01}
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{'loss': 1.7221, 'learning_rate': 0.000344, 'epoch': 0.01}
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{'loss': 1.8593, 'learning_rate': 0.000348, 'epoch': 0.01}
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{'loss': 1.7383, 'learning_rate': 0.00035200000000000005, 'epoch': 0.01}
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{'loss': 1.987, 'learning_rate': 0.00035600000000000003, 'epoch': 0.01}
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{'loss': 1.8862, 'learning_rate': 0.00036, 'epoch': 0.01}
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{'loss': 1.6766, 'learning_rate': 0.000364, 'epoch': 0.01}
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{'loss': 1.8663, 'learning_rate': 0.00036800000000000005, 'epoch': 0.01}
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{'loss': 1.9523, 'learning_rate': 0.00037200000000000004, 'epoch': 0.01}
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{'loss': 1.7663, 'learning_rate': 0.000376, 'epoch': 0.01}
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{'loss': 1.803, 'learning_rate': 0.00038, 'epoch': 0.01}
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{'loss': 1.87, 'learning_rate': 0.000384, 'epoch': 0.01}
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{'loss': 1.9695, 'learning_rate': 0.000388, 'epoch': 0.01}
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{'loss': 1.8292, 'learning_rate': 0.000392, 'epoch': 0.01}
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{'loss': 1.8299, 'learning_rate': 0.00039600000000000003, 'epoch': 0.01}
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{'loss': 1.8092, 'learning_rate': 0.0004, 'epoch': 0.01}
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{'loss': 1.912, 'learning_rate': 0.00039999997787532754, 'epoch': 0.01}
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{'loss': 1.7853, 'learning_rate': 0.00039999991150131497, 'epoch': 0.02}
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{'loss': 1.8775, 'learning_rate': 0.00039999980087797706, 'epoch': 0.02}
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{'loss': 1.786, 'learning_rate': 0.00039999964600533815, 'epoch': 0.02}
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{'loss': 1.8799, 'learning_rate': 0.0003999994468834327, 'epoch': 0.02}
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{'loss': 1.872, 'learning_rate': 0.00039999920351230456, 'epoch': 0.02}
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{'loss': 1.7817, 'learning_rate': 0.00039999891589200773, 'epoch': 0.02}
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{'loss': 1.9934, 'learning_rate': 0.0003999985840226058, 'epoch': 0.02}
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{'loss': 1.7716, 'learning_rate': 0.0003999982079041722, 'epoch': 0.02}
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{'loss': 1.8222, 'learning_rate': 0.0003999977875367901, 'epoch': 0.02}
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{'loss': 1.8632, 'learning_rate': 0.0003999973229205525, 'epoch': 0.02}
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{'loss': 1.7595, 'learning_rate': 0.0003999968140555623, 'epoch': 0.02}
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{'loss': 1.6849, 'learning_rate': 0.00039999626094193197, 'epoch': 0.02}
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{'loss': 1.9866, 'learning_rate': 0.0003999956635797839, 'epoch': 0.02}
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{'loss': 1.8149, 'learning_rate': 0.0003999950219692503, 'epoch': 0.02}
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{'loss': 1.8287, 'learning_rate': 0.00039999433611047315, 'epoch': 0.02}
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{'loss': 1.7472, 'learning_rate': 0.00039999360600360414, 'epoch': 0.02}
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{'loss': 1.7806, 'learning_rate': 0.0003999928316488048, 'epoch': 0.02}
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{'loss': 1.9447, 'learning_rate': 0.00039999201304624643, 'epoch': 0.02}
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{'loss': 1.8369, 'learning_rate': 0.0003999911501961102, 'epoch': 0.02}
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{'loss': 1.8782, 'learning_rate': 0.000399990243098587, 'epoch': 0.02}
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{'loss': 1.8528, 'learning_rate': 0.0003999892917538776, 'epoch': 0.02}
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{'loss': 1.8133, 'learning_rate': 0.0003999882961621923, 'epoch': 0.02}
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{'loss': 1.6053, 'learning_rate': 0.0003999872563237514, 'epoch': 0.02}
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{'loss': 1.7234, 'learning_rate': 0.0003999861722387852, 'epoch': 0.02}
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{'loss': 1.9498, 'learning_rate': 0.0003999850439075333, 'epoch': 0.02}
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{'loss': 1.7752, 'learning_rate': 0.00039998387133024545, 'epoch': 0.02}
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{'loss': 1.837, 'learning_rate': 0.000399982654507181, 'epoch': 0.02}
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{'loss': 1.8002, 'learning_rate': 0.0003999813934386092, 'epoch': 0.02}
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{'loss': 1.9792, 'learning_rate': 0.00039998008812480913, 'epoch': 0.02}
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{'loss': 1.7035, 'learning_rate': 0.0003999787385660695, 'epoch': 0.02}
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{'loss': 1.7462, 'learning_rate': 0.000399977344762689, 'epoch': 0.02}
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{'loss': 1.9268, 'learning_rate': 0.00039997590671497584, 'epoch': 0.02}
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{'loss': 1.6444, 'learning_rate': 0.0003999744244232483, 'epoch': 0.02}
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{'loss': 1.6023, 'learning_rate': 0.0003999728978878343, 'epoch': 0.02}
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{'loss': 1.9378, 'learning_rate': 0.0003999713271090716, 'epoch': 0.02}
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{'loss': 1.8392, 'learning_rate': 0.00039996971208730776, 'epoch': 0.02}
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{'loss': 1.9371, 'learning_rate': 0.0003999680528229, 'epoch': 0.02}
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{'loss': 1.8793, 'learning_rate': 0.00039996634931621546, 'epoch': 0.02}
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{'loss': 1.7281, 'learning_rate': 0.00039996460156763115, 'epoch': 0.02}
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{'loss': 1.8999, 'learning_rate': 0.00039996280957753356, 'epoch': 0.02}
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{'loss': 1.7616, 'learning_rate': 0.0003999609733463193, 'epoch': 0.02}
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{'loss': 1.8009, 'learning_rate': 0.0003999590928743946, 'epoch': 0.02}
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{'loss': 1.8248, 'learning_rate': 0.00039995716816217553, 'epoch': 0.02}
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{'loss': 1.8125, 'learning_rate': 0.00039995519921008784, 'epoch': 0.02}
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{'loss': 1.8755, 'learning_rate': 0.00039995318601856723, 'epoch': 0.02}
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{'loss': 1.8212, 'learning_rate': 0.00039995112858805915, 'epoch': 0.02}
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{'loss': 1.8124, 'learning_rate': 0.00039994902691901864, 'epoch': 0.02}
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{'loss': 2.0968, 'learning_rate': 0.00039994688101191087, 'epoch': 0.02}
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{'loss': 1.9205, 'learning_rate': 0.0003999446908672105, 'epoch': 0.02}
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{'loss': 1.7214, 'learning_rate': 0.0003999424564854022, 'epoch': 0.02}
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{'loss': 1.9117, 'learning_rate': 0.00039994017786698015, 'epoch': 0.02}
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{'loss': 1.8926, 'learning_rate': 0.00039993785501244865, 'epoch': 0.02}
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{'loss': 1.7361, 'learning_rate': 0.0003999354879223215, 'epoch': 0.02}
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{'loss': 1.7801, 'learning_rate': 0.00039993307659712246, 'epoch': 0.02}
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{'loss': 1.7732, 'learning_rate': 0.00039993062103738515, 'epoch': 0.02}
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{'loss': 1.8174, 'learning_rate': 0.0003999281212436526, 'epoch': 0.02}
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{'loss': 1.876, 'learning_rate': 0.00039992557721647815, 'epoch': 0.02}
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{'loss': 1.963, 'learning_rate': 0.00039992298895642444, 'epoch': 0.02}
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{'loss': 1.9794, 'learning_rate': 0.0003999203564640643, 'epoch': 0.02}
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{'loss': 1.9807, 'learning_rate': 0.00039991767973998, 'epoch': 0.02}
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{'loss': 1.8689, 'learning_rate': 0.0003999149587847638, 'epoch': 0.02}
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{'loss': 1.8105, 'learning_rate': 0.0003999121935990178, 'epoch': 0.02}
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{'loss': 1.8673, 'learning_rate': 0.00039990938418335364, 'epoch': 0.02}
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{'loss': 1.7556, 'learning_rate': 0.00039990653053839295, 'epoch': 0.02}
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{'loss': 1.8107, 'learning_rate': 0.00039990363266476716, 'epoch': 0.02}
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{'loss': 1.7058, 'learning_rate': 0.00039990069056311734, 'epoch': 0.02}
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{'loss': 1.8396, 'learning_rate': 0.0003998977042340944, 'epoch': 0.02}
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{'loss': 1.8712, 'learning_rate': 0.00039989467367835917, 'epoch': 0.02}
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{'loss': 1.7696, 'learning_rate': 0.00039989159889658205, 'epoch': 0.03}
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{'loss': 2.0015, 'learning_rate': 0.0003998884798894434, 'epoch': 0.03}
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{'loss': 1.7819, 'learning_rate': 0.0003998853166576332, 'epoch': 0.03}
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{'loss': 1.8661, 'learning_rate': 0.0003998788575228074, 'epoch': 0.03}
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{'loss': 1.7113, 'learning_rate': 0.00039987556162122105, 'epoch': 0.03}
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{'loss': 1.8855, 'learning_rate': 0.0003998722214978212, 'epoch': 0.03}
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{'loss': 1.8185, 'learning_rate': 0.00039986883715334697, 'epoch': 0.03}
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{'loss': 1.9077, 'learning_rate': 0.00039986540858854706, 'epoch': 0.03}
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{'loss': 1.8344, 'learning_rate': 0.00039985841880101454, 'epoch': 0.03}
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{'loss': 1.6801, 'learning_rate': 0.00039985485757982833, 'epoch': 0.03}
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{'loss': 1.8112, 'learning_rate': 0.0003998512521414095, 'epoch': 0.03}
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{'loss': 1.8427, 'learning_rate': 0.0003998476024865556, 'epoch': 0.03}
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{'loss': 1.8487, 'learning_rate': 0.00039984390861607424, 'epoch': 0.03}
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{'loss': 1.8618, 'learning_rate': 0.0003998401705307825, 'epoch': 0.03}
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{'loss': 1.9246, 'learning_rate': 0.00039983256171908637, 'epoch': 0.03}
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{'loss': 1.777, 'learning_rate': 0.0003998286909943653, 'epoch': 0.03}
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{'loss': 1.888, 'learning_rate': 0.00039982477605820084, 'epoch': 0.03}
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{'loss': 1.802, 'learning_rate': 0.0003998168135550161, 'epoch': 0.03}
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{'loss': 1.9086, 'learning_rate': 0.0003998127659897575, 'epoch': 0.03}
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{'loss': 1.8168, 'learning_rate': 0.00039980867421657887, 'epoch': 0.03}
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{'loss': 1.844, 'learning_rate': 0.0003998045382363855, 'epoch': 0.03}
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{'loss': 1.6602, 'learning_rate': 0.00039980035805009236, 'epoch': 0.03}
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{'loss': 1.82, 'learning_rate': 0.00039979613365862443, 'epoch': 0.03}
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{'loss': 1.5808, 'learning_rate': 0.00039979186506291635, 'epoch': 0.03}
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{'loss': 1.8157, 'learning_rate': 0.00039978755226391236, 'epoch': 0.03}
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{'loss': 1.7821, 'learning_rate': 0.0003997831952625669, 'epoch': 0.03}
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{'loss': 1.7804, 'learning_rate': 0.00039977879405984375, 'epoch': 0.03}
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{'loss': 1.9383, 'learning_rate': 0.0003997743486567167, 'epoch': 0.03}
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{'loss': 1.8185, 'learning_rate': 0.0003997698590541693, 'epoch': 0.03}
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{'loss': 1.6616, 'learning_rate': 0.0003997653252531949, 'epoch': 0.03}
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{'loss': 1.8869, 'learning_rate': 0.00039976074725479654, 'epoch': 0.03}
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{'loss': 1.7009, 'learning_rate': 0.0003997561250599871, 'epoch': 0.03}
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{'loss': 1.9382, 'learning_rate': 0.0003997514586697892, 'epoch': 0.03}
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{'loss': 1.8235, 'learning_rate': 0.00039974674808523534, 'epoch': 0.03}
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{'loss': 1.771, 'learning_rate': 0.0003997419933073676, 'epoch': 0.03}
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{'loss': 1.715, 'learning_rate': 0.0003997371943372381, 'epoch': 0.03}
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{'loss': 1.6947, 'learning_rate': 0.0003997323511759085, 'epoch': 0.03}
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{'loss': 1.7607, 'learning_rate': 0.00039972746382445037, 'epoch': 0.03}
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{'loss': 1.6536, 'learning_rate': 0.000399722532283945, 'epoch': 0.03}
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{'loss': 1.8122, 'learning_rate': 0.00039971755655548346, 'epoch': 0.03}
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{'loss': 1.8806, 'learning_rate': 0.0003997125366401667, 'epoch': 0.03}
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{'loss': 1.8513, 'learning_rate': 0.0003997074725391053, 'epoch': 0.03}
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{'loss': 1.8634, 'learning_rate': 0.00039970236425341957, 'epoch': 0.03}
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{'loss': 1.9743, 'learning_rate': 0.00039969721178423985, 'epoch': 0.03}
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{'loss': 1.743, 'learning_rate': 0.00039969201513270617, 'epoch': 0.03}
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{'loss': 1.6621, 'learning_rate': 0.00039968677429996806, 'epoch': 0.03}
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{'loss': 1.8157, 'learning_rate': 0.0003996814892871852, 'epoch': 0.03}
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{'loss': 1.8073, 'learning_rate': 0.0003996761600955268, 'epoch': 0.03}
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{'loss': 1.8465, 'learning_rate': 0.0003996707867261719, 'epoch': 0.03}
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{'loss': 1.6805, 'learning_rate': 0.0003996653691803095, 'epoch': 0.03}
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{'loss': 1.9336, 'learning_rate': 0.000399659907459138, 'epoch': 0.03}
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{'loss': 1.8547, 'learning_rate': 0.000399654401563866, 'epoch': 0.03}
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{'loss': 1.8622, 'learning_rate': 0.00039964885149571146, 'epoch': 0.03}
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{'loss': 1.7799, 'learning_rate': 0.0003996432572559025, 'epoch': 0.03}
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{'loss': 1.864, 'learning_rate': 0.00039963761884567663, 'epoch': 0.03}
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{'loss': 1.8255, 'learning_rate': 0.00039963193626628153, 'epoch': 0.03}
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{'loss': 1.7513, 'learning_rate': 0.0003996262095189743, 'epoch': 0.03}
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{'loss': 1.9518, 'learning_rate': 0.0003996204386050221, 'epoch': 0.03}
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{'loss': 1.8381, 'learning_rate': 0.00039961462352570157, 'epoch': 0.03}
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{'loss': 1.8554, 'learning_rate': 0.0003996087642822994, 'epoch': 0.03}
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{'loss': 1.7689, 'learning_rate': 0.0003996028608761119, 'epoch': 0.03}
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{'loss': 1.8383, 'learning_rate': 0.0003995969133084451, 'epoch': 0.03}
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{'loss': 1.8717, 'learning_rate': 0.00039958488569394714, 'epoch': 0.03}
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{'loss': 1.793, 'learning_rate': 0.000399578805649777, 'epoch': 0.04}
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{'loss': 1.8575, 'learning_rate': 0.0003995726814494498, 'epoch': 0.04}
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{'loss': 1.7864, 'learning_rate': 0.0003988509729124991, 'epoch': 0.05}
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{'loss': 1.8593, 'learning_rate': 0.0003988408813924838, 'epoch': 0.05}
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{'loss': 1.8248, 'learning_rate': 0.0003988307458795747, 'epoch': 0.05}
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{'loss': 1.7911, 'learning_rate': 0.00039882056637601426, 'epoch': 0.05}
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{'loss': 1.7673, 'learning_rate': 0.0003988103428840547, 'epoch': 0.05}
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{'loss': 1.8589, 'learning_rate': 0.00039880007540595794, 'epoch': 0.05}
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{'loss': 1.8383, 'learning_rate': 0.00039878976394399555, 'epoch': 0.05}
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{'loss': 1.6251, 'learning_rate': 0.000398779408500449, 'epoch': 0.05}
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{'loss': 1.7892, 'learning_rate': 0.0003987690090776093, 'epoch': 0.05}
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{'loss': 1.7274, 'learning_rate': 0.00039875856567777744, 'epoch': 0.05}
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{'loss': 1.8624, 'learning_rate': 0.0003987480783032638, 'epoch': 0.05}
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{'loss': 1.8218, 'learning_rate': 0.0003987375469563888, 'epoch': 0.05}
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{'loss': 1.8543, 'learning_rate': 0.00039872697163948243, 'epoch': 0.05}
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{'loss': 1.8423, 'learning_rate': 0.0003987163523548845, 'epoch': 0.05}
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{'loss': 1.8593, 'learning_rate': 0.00039870568910494434, 'epoch': 0.05}
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{'loss': 1.7345, 'learning_rate': 0.00039869498189202136, 'epoch': 0.05}
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{'loss': 1.8453, 'learning_rate': 0.0003986842307184843, 'epoch': 0.05}
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{'loss': 1.9135, 'learning_rate': 0.00039867343558671204, 'epoch': 0.05}
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{'loss': 1.8207, 'learning_rate': 0.0003986625964990927, 'epoch': 0.05}
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{'loss': 1.6494, 'learning_rate': 0.0003986517134580247, 'epoch': 0.05}
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{'loss': 1.79, 'learning_rate': 0.0003986407864659156, 'epoch': 0.05}
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{'loss': 1.6841, 'learning_rate': 0.0003986298155251831, 'epoch': 0.05}
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{'loss': 1.7476, 'learning_rate': 0.0003986188006382545, 'epoch': 0.05}
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{'loss': 1.7944, 'learning_rate': 0.0003986077418075667, 'epoch': 0.05}
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{'loss': 1.9451, 'learning_rate': 0.00039859663903556657, 'epoch': 0.05}
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{'loss': 1.965, 'learning_rate': 0.0003985854923247105, 'epoch': 0.05}
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{'loss': 1.734, 'learning_rate': 0.00039857430167746454, 'epoch': 0.05}
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{'loss': 1.8918, 'learning_rate': 0.00039856306709630475, 'epoch': 0.05}
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{'loss': 1.8399, 'learning_rate': 0.0003985517885837167, 'epoch': 0.05}
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{'loss': 1.753, 'learning_rate': 0.0003985404661421957, 'epoch': 0.05}
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{'loss': 1.781, 'learning_rate': 0.00039852909977424687, 'epoch': 0.05}
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{'loss': 1.7894, 'learning_rate': 0.0003985176894823849, 'epoch': 0.05}
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{'loss': 1.854, 'learning_rate': 0.00039850623526913433, 'epoch': 0.05}
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{'loss': 1.7999, 'learning_rate': 0.00039849473713702936, 'epoch': 0.05}
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{'loss': 1.8435, 'learning_rate': 0.00039848319508861387, 'epoch': 0.05}
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{'loss': 1.8206, 'learning_rate': 0.0003984716091264415, 'epoch': 0.05}
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{'loss': 1.7712, 'learning_rate': 0.0003984599792530757, 'epoch': 0.05}
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{'loss': 1.6843, 'learning_rate': 0.0003984483054710895, 'epoch': 0.05}
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{'loss': 1.7151, 'learning_rate': 0.0003984365877830656, 'epoch': 0.05}
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{'loss': 1.7526, 'learning_rate': 0.0003984248261915966, 'epoch': 0.05}
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{'loss': 1.8997, 'learning_rate': 0.00039841302069928465, 'epoch': 0.05}
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{'loss': 1.7865, 'learning_rate': 0.00039840117130874176, 'epoch': 0.05}
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{'loss': 1.8472, 'learning_rate': 0.00039838927802258946, 'epoch': 0.05}
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{'loss': 1.9315, 'learning_rate': 0.0003983773408434592, 'epoch': 0.05}
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{'loss': 1.7279, 'learning_rate': 0.00039836535977399193, 'epoch': 0.05}
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{'loss': 1.8795, 'learning_rate': 0.0003983533348168386, 'epoch': 0.06}
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{'loss': 1.8414, 'learning_rate': 0.0003983412659746595, 'epoch': 0.06}
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{'loss': 1.7834, 'learning_rate': 0.0003983169966459148, 'epoch': 0.06}
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{'loss': 1.6585, 'learning_rate': 0.0003983047961647186, 'epoch': 0.06}
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{'loss': 1.8102, 'learning_rate': 0.00039829255180923574, 'epoch': 0.06}
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{'loss': 1.8267, 'learning_rate': 0.00039828026358217533, 'epoch': 0.06}
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{'loss': 1.772, 'learning_rate': 0.0003982679314862559, 'epoch': 0.06}
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{'loss': 1.7212, 'learning_rate': 0.00039825555552420604, 'epoch': 0.06}
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{'loss': 1.8234, 'learning_rate': 0.0003982431356987638, 'epoch': 0.06}
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{'loss': 1.8071, 'learning_rate': 0.00039823067201267713, 'epoch': 0.06}
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{'loss': 1.7077, 'learning_rate': 0.00039821816446870346, 'epoch': 0.06}
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{'loss': 1.741, 'learning_rate': 0.0003982056130696101, 'epoch': 0.06}
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{'loss': 1.862, 'learning_rate': 0.0003981930178181741, 'epoch': 0.06}
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{'loss': 1.8635, 'learning_rate': 0.0003981803787171819, 'epoch': 0.06}
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{'loss': 1.8943, 'learning_rate': 0.00039816769576943, 'epoch': 0.06}
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{'loss': 1.7162, 'learning_rate': 0.00039815496897772457, 'epoch': 0.06}
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{'loss': 1.7632, 'learning_rate': 0.0003979588077655018, 'epoch': 0.06}
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{'loss': 1.7821, 'learning_rate': 0.0003979453798600756, 'epoch': 0.06}
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{'loss': 1.8344, 'learning_rate': 0.00039793190815988233, 'epoch': 0.06}
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{'loss': 1.6997, 'learning_rate': 0.0003979183926679027, 'epoch': 0.06}
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{'loss': 1.956, 'learning_rate': 0.0003979048333871269, 'epoch': 0.06}
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{'loss': 1.756, 'learning_rate': 0.00039789123032055493, 'epoch': 0.06}
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{'loss': 1.8861, 'learning_rate': 0.00039787758347119626, 'epoch': 0.06}
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{'loss': 1.6501, 'learning_rate': 0.00039786389284207044, 'epoch': 0.06}
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{'loss': 1.8189, 'learning_rate': 0.0003978501584362063, 'epoch': 0.06}
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{'loss': 1.6048, 'learning_rate': 0.0003978363802566426, 'epoch': 0.06}
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{'loss': 1.7401, 'learning_rate': 0.00039782255830642777, 'epoch': 0.06}
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{'loss': 1.8954, 'learning_rate': 0.0003978086925886198, 'epoch': 0.06}
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{'loss': 1.8313, 'learning_rate': 0.00039779478310628645, 'epoch': 0.06}
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{'loss': 1.9141, 'learning_rate': 0.00039778082986250513, 'epoch': 0.06}
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{'loss': 1.6629, 'learning_rate': 0.00039776683286036295, 'epoch': 0.06}
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{'loss': 1.8725, 'learning_rate': 0.00039775279210295676, 'epoch': 0.06}
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{'loss': 1.6964, 'learning_rate': 0.00039773870759339297, 'epoch': 0.06}
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{'loss': 1.8059, 'learning_rate': 0.0003977245793347878, 'epoch': 0.06}
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{'loss': 1.7852, 'learning_rate': 0.00039771040733026697, 'epoch': 0.06}
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{'loss': 1.9568, 'learning_rate': 0.000397696191582966, 'epoch': 0.06}
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{'loss': 1.8273, 'learning_rate': 0.0003976819320960303, 'epoch': 0.06}
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{'loss': 1.8533, 'learning_rate': 0.00039766762887261445, 'epoch': 0.06}
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{'loss': 1.7547, 'learning_rate': 0.00039765328191588314, 'epoch': 0.06}
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{'loss': 1.8107, 'learning_rate': 0.0003976388912290105, 'epoch': 0.06}
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{'loss': 2.0183, 'learning_rate': 0.00039762445681518053, 'epoch': 0.06}
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{'loss': 1.7311, 'learning_rate': 0.0003976099786775867, 'epoch': 0.06}
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{'loss': 1.9018, 'learning_rate': 0.00039759545681943237, 'epoch': 0.06}
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{'loss': 1.6872, 'learning_rate': 0.00039758089124393035, 'epoch': 0.06}
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{'loss': 1.7358, 'learning_rate': 0.00039756628195430324, 'epoch': 0.06}
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{'loss': 1.6796, 'learning_rate': 0.00039755162895378326, 'epoch': 0.06}
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{'loss': 1.892, 'learning_rate': 0.0003975369322456125, 'epoch': 0.06}
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{'loss': 1.7282, 'learning_rate': 0.0003975221918330424, 'epoch': 0.06}
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{'loss': 1.9827, 'learning_rate': 0.00039750740771933417, 'epoch': 0.06}
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{'loss': 1.6816, 'learning_rate': 0.000397492579907759, 'epoch': 0.06}
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{'loss': 1.799, 'learning_rate': 0.0003974777084015973, 'epoch': 0.06}
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{'loss': 1.7513, 'learning_rate': 0.00039746279320413937, 'epoch': 0.06}
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{'loss': 1.8015, 'learning_rate': 0.00039744783431868515, 'epoch': 0.06}
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{'loss': 1.9568, 'learning_rate': 0.0003974328317485443, 'epoch': 0.07}
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{'loss': 1.7025, 'learning_rate': 0.0003974177854970361, 'epoch': 0.07}
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{'loss': 1.7496, 'learning_rate': 0.0003974026955674893, 'epoch': 0.07}
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{'loss': 1.7982, 'learning_rate': 0.00039738756196324267, 'epoch': 0.07}
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{'loss': 1.7978, 'learning_rate': 0.00039737238468764453, 'epoch': 0.07}
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{'loss': 1.8577, 'learning_rate': 0.0003973571637440526, 'epoch': 0.07}
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{'loss': 1.8767, 'learning_rate': 0.00039734189913583464, 'epoch': 0.07}
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{'loss': 1.7078, 'learning_rate': 0.0003973265908663678, 'epoch': 0.07}
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{'loss': 1.8624, 'learning_rate': 0.000397311238939039, 'epoch': 0.07}
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{'loss': 1.8064, 'learning_rate': 0.0003972958433572448, 'epoch': 0.07}
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{'loss': 1.8586, 'learning_rate': 0.00039728040412439147, 'epoch': 0.07}
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{'loss': 1.7813, 'learning_rate': 0.0003972649212438948, 'epoch': 0.07}
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{'loss': 1.7999, 'learning_rate': 0.00039724939471918043, 'epoch': 0.07}
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{'loss': 1.8336, 'learning_rate': 0.0003972338245536835, 'epoch': 0.07}
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{'loss': 1.7335, 'learning_rate': 0.00039721821075084886, 'epoch': 0.07}
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{'loss': 1.727, 'learning_rate': 0.00039720255331413104, 'epoch': 0.07}
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{'loss': 1.8477, 'learning_rate': 0.0003971868522469941, 'epoch': 0.07}
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{'loss': 1.6951, 'learning_rate': 0.000397171107552912, 'epoch': 0.07}
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{'loss': 1.6504, 'learning_rate': 0.00039715531923536807, 'epoch': 0.07}
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{'loss': 1.9051, 'learning_rate': 0.00039713948729785546, 'epoch': 0.07}
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{'loss': 1.8366, 'learning_rate': 0.000397123611743877, 'epoch': 0.07}
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{'loss': 1.8481, 'learning_rate': 0.000397107692576945, 'epoch': 0.07}
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{'loss': 1.8254, 'learning_rate': 0.00039709172980058164, 'epoch': 0.07}
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{'loss': 1.8252, 'learning_rate': 0.0003970757234183185, 'epoch': 0.07}
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{'loss': 1.6986, 'learning_rate': 0.00039705967343369705, 'epoch': 0.07}
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{'loss': 1.7434, 'learning_rate': 0.0003970435798502683, 'epoch': 0.07}
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{'loss': 1.7413, 'learning_rate': 0.0003970274426715928, 'epoch': 0.07}
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{'loss': 1.7657, 'learning_rate': 0.00039701126190124094, 'epoch': 0.07}
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{'loss': 1.7052, 'learning_rate': 0.00039699503754279264, 'epoch': 0.07}
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{'loss': 1.8257, 'learning_rate': 0.0003969787695998374, 'epoch': 0.07}
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{'loss': 1.8254, 'learning_rate': 0.0003969624580759746, 'epoch': 0.07}
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{'loss': 1.8684, 'learning_rate': 0.00039694610297481305, 'epoch': 0.07}
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{'loss': 1.8561, 'learning_rate': 0.0003969297042999712, 'epoch': 0.07}
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{'loss': 1.7693, 'learning_rate': 0.00039691326205507717, 'epoch': 0.07}
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{'loss': 1.8749, 'learning_rate': 0.00039689677624376896, 'epoch': 0.07}
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{'loss': 1.8235, 'learning_rate': 0.00039688024686969386, 'epoch': 0.07}
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{'loss': 1.6995, 'learning_rate': 0.00039686367393650893, 'epoch': 0.07}
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{'loss': 1.5403, 'learning_rate': 0.0003968470574478809, 'epoch': 0.07}
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{'loss': 1.8066, 'learning_rate': 0.00039683039740748613, 'epoch': 0.07}
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{'loss': 1.8615, 'learning_rate': 0.0003968136938190106, 'epoch': 0.07}
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{'loss': 1.5913, 'learning_rate': 0.00039679694668614987, 'epoch': 0.07}
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{'loss': 1.8386, 'learning_rate': 0.00039678015601260925, 'epoch': 0.07}
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{'loss': 1.8947, 'learning_rate': 0.00039676332180210364, 'epoch': 0.07}
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{'loss': 1.8435, 'learning_rate': 0.0003967464440583574, 'epoch': 0.07}
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{'loss': 1.7903, 'learning_rate': 0.00039672952278510494, 'epoch': 0.07}
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{'loss': 1.8439, 'learning_rate': 0.00039671255798608975, 'epoch': 0.07}
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{'loss': 1.8488, 'learning_rate': 0.00039669554966506544, 'epoch': 0.07}
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{'loss': 1.7086, 'learning_rate': 0.000396678497825795, 'epoch': 0.07}
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{'loss': 1.792, 'learning_rate': 0.000396661402472051, 'epoch': 0.07}
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{'loss': 1.8584, 'learning_rate': 0.00039664426360761586, 'epoch': 0.07}
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{'loss': 1.629, 'learning_rate': 0.0003966270812362814, 'epoch': 0.07}
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{'loss': 1.6584, 'learning_rate': 0.0003966098553618493, 'epoch': 0.07}
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{'loss': 1.6464, 'learning_rate': 0.00039659258598813055, 'epoch': 0.07}
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{'loss': 1.7918, 'learning_rate': 0.00039657527311894606, 'epoch': 0.07}
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{'loss': 1.6825, 'learning_rate': 0.00039655791675812614, 'epoch': 0.07}
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{'loss': 1.7429, 'learning_rate': 0.00039654051690951093, 'epoch': 0.07}
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{'loss': 1.7522, 'learning_rate': 0.00039652307357695006, 'epoch': 0.07}
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{'loss': 1.723, 'learning_rate': 0.00039650558676430285, 'epoch': 0.07}
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{'loss': 1.6514, 'learning_rate': 0.0003964880564754381, 'epoch': 0.07}
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{'loss': 1.7737, 'learning_rate': 0.0003964704827142344, 'epoch': 0.07}
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{'loss': 1.9399, 'learning_rate': 0.00039645286548457994, 'epoch': 0.07}
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{'loss': 1.7434, 'learning_rate': 0.0003964352047903723, 'epoch': 0.07}
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{'loss': 1.8614, 'learning_rate': 0.000396417500635519, 'epoch': 0.07}
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{'loss': 1.7248, 'learning_rate': 0.000396399753023937, 'epoch': 0.07}
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{'loss': 1.8147, 'learning_rate': 0.00039638196195955293, 'epoch': 0.07}
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{'loss': 1.7088, 'learning_rate': 0.0003963641274463029, 'epoch': 0.07}
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{'loss': 1.6859, 'learning_rate': 0.0003963462494881328, 'epoch': 0.07}
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{'loss': 1.8509, 'learning_rate': 0.00039632832808899807, 'epoch': 0.07}
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{'loss': 1.7807, 'learning_rate': 0.0003963103632528638, 'epoch': 0.08}
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{'loss': 1.8307, 'learning_rate': 0.00039629235498370456, 'epoch': 0.08}
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{'loss': 1.776, 'learning_rate': 0.0003962743032855047, 'epoch': 0.08}
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{'loss': 1.7817, 'learning_rate': 0.000396256208162258, 'epoch': 0.08}
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{'loss': 1.7335, 'learning_rate': 0.00039623806961796806, 'epoch': 0.08}
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{'loss': 1.7618, 'learning_rate': 0.000396219887656648, 'epoch': 0.08}
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{'loss': 1.7928, 'learning_rate': 0.0003962016622823204, 'epoch': 0.08}
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{'loss': 1.7305, 'learning_rate': 0.0003961833934990176, 'epoch': 0.08}
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{'loss': 1.8676, 'learning_rate': 0.00039616508131078154, 'epoch': 0.08}
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{'loss': 1.8546, 'learning_rate': 0.00039614672572166364, 'epoch': 0.08}
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{'loss': 1.7474, 'learning_rate': 0.0003961283267357252, 'epoch': 0.08}
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{'loss': 1.7562, 'learning_rate': 0.0003961098843570367, 'epoch': 0.08}
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{'loss': 1.7885, 'learning_rate': 0.00039609139858967873, 'epoch': 0.08}
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{'loss': 1.9507, 'learning_rate': 0.00039607286943774096, 'epoch': 0.08}
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{'loss': 1.7405, 'learning_rate': 0.000396054296905323, 'epoch': 0.08}
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{'loss': 1.6542, 'learning_rate': 0.00039603568099653394, 'epoch': 0.08}
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{'loss': 1.9583, 'learning_rate': 0.0003960170217154926, 'epoch': 0.08}
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{'loss': 1.8323, 'learning_rate': 0.0003959983190663271, 'epoch': 0.08}
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{'loss': 1.8341, 'learning_rate': 0.0003959795730531755, 'epoch': 0.08}
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{'loss': 1.7341, 'learning_rate': 0.0003959607836801852, 'epoch': 0.08}
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{'loss': 1.913, 'learning_rate': 0.0003959419509515133, 'epoch': 0.08}
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{'loss': 1.8376, 'learning_rate': 0.0003959230748713265, 'epoch': 0.08}
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{'loss': 1.8546, 'learning_rate': 0.0003959041554438011, 'epoch': 0.08}
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{'loss': 1.6754, 'learning_rate': 0.0003958851926731229, 'epoch': 0.08}
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{'loss': 1.772, 'learning_rate': 0.00039586618656348735, 'epoch': 0.08}
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{'loss': 1.7421, 'learning_rate': 0.00039584713711909956, 'epoch': 0.08}
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{'loss': 1.7301, 'learning_rate': 0.0003958280443441741, 'epoch': 0.08}
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{'loss': 1.7809, 'learning_rate': 0.00039580890824293517, 'epoch': 0.08}
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{'loss': 1.956, 'learning_rate': 0.00039578972881961665, 'epoch': 0.08}
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{'loss': 1.8369, 'learning_rate': 0.0003957705060784619, 'epoch': 0.08}
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{'loss': 1.8083, 'learning_rate': 0.0003957512400237238, 'epoch': 0.08}
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{'loss': 1.9556, 'learning_rate': 0.00039573193065966497, 'epoch': 0.08}
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{'loss': 1.7622, 'learning_rate': 0.00039571257799055754, 'epoch': 0.08}
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{'loss': 1.8417, 'learning_rate': 0.0003956931820206832, 'epoch': 0.08}
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{'loss': 1.8039, 'learning_rate': 0.0003956737427543333, 'epoch': 0.08}
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{'loss': 1.6701, 'learning_rate': 0.0003956542601958087, 'epoch': 0.08}
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{'loss': 1.7418, 'learning_rate': 0.0003956347343494198, 'epoch': 0.08}
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{'loss': 1.7193, 'learning_rate': 0.0003956151652194866, 'epoch': 0.08}
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{'loss': 1.7874, 'learning_rate': 0.0003955955528103389, 'epoch': 0.08}
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{'loss': 1.7425, 'learning_rate': 0.0003955758971263157, 'epoch': 0.08}
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{'loss': 1.9046, 'learning_rate': 0.00039555619817176576, 'epoch': 0.08}
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{'loss': 1.6623, 'learning_rate': 0.00039553645595104747, 'epoch': 0.08}
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{'loss': 1.7682, 'learning_rate': 0.00039551667046852873, 'epoch': 0.08}
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{'loss': 1.8296, 'learning_rate': 0.000395496841728587, 'epoch': 0.08}
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{'loss': 1.8189, 'learning_rate': 0.0003954769697356093, 'epoch': 0.08}
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{'loss': 1.7958, 'learning_rate': 0.0003954570544939923, 'epoch': 0.08}
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{'loss': 1.7713, 'learning_rate': 0.00039543709600814214, 'epoch': 0.08}
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{'loss': 1.7116, 'learning_rate': 0.0003954170942824746, 'epoch': 0.08}
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{'loss': 1.7419, 'learning_rate': 0.00039539704932141487, 'epoch': 0.08}
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{'loss': 1.9713, 'learning_rate': 0.00039537696112939804, 'epoch': 0.08}
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{'loss': 1.9347, 'learning_rate': 0.00039535682971086845, 'epoch': 0.08}
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{'loss': 1.775, 'learning_rate': 0.00039533665507028007, 'epoch': 0.08}
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{'loss': 1.73, 'learning_rate': 0.00039531643721209654, 'epoch': 0.08}
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{'loss': 1.7471, 'learning_rate': 0.000395296176140791, 'epoch': 0.08}
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{'loss': 1.817, 'learning_rate': 0.00039527587186084605, 'epoch': 0.08}
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{'loss': 1.7526, 'learning_rate': 0.00039525552437675405, 'epoch': 0.08}
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{'loss': 1.7034, 'learning_rate': 0.00039523513369301675, 'epoch': 0.08}
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{'loss': 1.7872, 'learning_rate': 0.00039521469981414556, 'epoch': 0.08}
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{'loss': 1.8387, 'learning_rate': 0.0003951942227446614, 'epoch': 0.08}
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{'loss': 1.8827, 'learning_rate': 0.0003951737024890948, 'epoch': 0.08}
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{'loss': 1.7602, 'learning_rate': 0.00039515313905198567, 'epoch': 0.08}
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{'loss': 1.6599, 'learning_rate': 0.00039513253243788374, 'epoch': 0.08}
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{'loss': 1.7409, 'learning_rate': 0.0003951118826513481, 'epoch': 0.08}
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{'loss': 1.8524, 'learning_rate': 0.00039509118969694736, 'epoch': 0.08}
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{'loss': 1.718, 'learning_rate': 0.00039507045357926, 'epoch': 0.08}
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{'loss': 1.8281, 'learning_rate': 0.0003950496743028736, 'epoch': 0.08}
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{'loss': 1.7044, 'learning_rate': 0.0003950288518723856, 'epoch': 0.08}
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{'loss': 1.6658, 'learning_rate': 0.0003950079862924028, 'epoch': 0.08}
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{'loss': 1.8943, 'learning_rate': 0.00039498707756754176, 'epoch': 0.09}
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{'loss': 1.8424, 'learning_rate': 0.00039496612570242846, 'epoch': 0.09}
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{'loss': 1.8056, 'learning_rate': 0.00039494513070169833, 'epoch': 0.09}
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{'loss': 1.7077, 'learning_rate': 0.0003949240925699966, 'epoch': 0.09}
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{'loss': 1.7672, 'learning_rate': 0.0003949030113119777, 'epoch': 0.09}
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{'loss': 1.8221, 'learning_rate': 0.00039488188693230595, 'epoch': 0.09}
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{'loss': 1.6537, 'learning_rate': 0.00039486071943565495, 'epoch': 0.09}
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{'loss': 1.7519, 'learning_rate': 0.00039483950882670805, 'epoch': 0.09}
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{'loss': 1.7035, 'learning_rate': 0.0003948182551101579, 'epoch': 0.09}
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{'loss': 1.7506, 'learning_rate': 0.00039479695829070687, 'epoch': 0.09}
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{'loss': 1.7805, 'learning_rate': 0.0003947756183730668, 'epoch': 0.09}
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{'loss': 1.7556, 'learning_rate': 0.0003947542353619591, 'epoch': 0.09}
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{'loss': 1.9552, 'learning_rate': 0.0003947328092621147, 'epoch': 0.09}
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{'loss': 1.7991, 'learning_rate': 0.00039471134007827404, 'epoch': 0.09}
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{'loss': 1.8624, 'learning_rate': 0.00039468982781518705, 'epoch': 0.09}
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{'loss': 1.9038, 'learning_rate': 0.00039466827247761337, 'epoch': 0.09}
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{'loss': 1.9206, 'learning_rate': 0.0003946466740703219, 'epoch': 0.09}
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{'loss': 1.9064, 'learning_rate': 0.00039462503259809134, 'epoch': 0.09}
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{'loss': 1.7476, 'learning_rate': 0.0003946033480657097, 'epoch': 0.09}
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{'loss': 1.7746, 'learning_rate': 0.0003945816204779747, 'epoch': 0.09}
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{'loss': 1.7362, 'learning_rate': 0.00039455984983969346, 'epoch': 0.09}
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{'loss': 1.7308, 'learning_rate': 0.00039453803615568266, 'epoch': 0.09}
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{'loss': 1.6835, 'learning_rate': 0.00039451617943076845, 'epoch': 0.09}
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{'loss': 1.7648, 'learning_rate': 0.0003944942796697867, 'epoch': 0.09}
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{'loss': 1.7818, 'learning_rate': 0.0003944723368775825, 'epoch': 0.09}
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{'loss': 1.7973, 'learning_rate': 0.0003944503510590107, 'epoch': 0.09}
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{'loss': 1.9494, 'learning_rate': 0.00039442832221893567, 'epoch': 0.09}
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{'loss': 1.7235, 'learning_rate': 0.00039440625036223103, 'epoch': 0.09}
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{'loss': 1.6461, 'learning_rate': 0.00039438413549378027, 'epoch': 0.09}
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{'loss': 1.8894, 'learning_rate': 0.00039436197761847616, 'epoch': 0.09}
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{'loss': 1.7474, 'learning_rate': 0.00039433977674122105, 'epoch': 0.09}
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{'loss': 1.7687, 'learning_rate': 0.0003943175328669269, 'epoch': 0.09}
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{'loss': 1.8025, 'learning_rate': 0.00039429524600051495, 'epoch': 0.09}
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{'loss': 1.8003, 'learning_rate': 0.0003942729161469162, 'epoch': 0.09}
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{'loss': 1.8271, 'learning_rate': 0.000394250543311071, 'epoch': 0.09}
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{'loss': 1.7797, 'learning_rate': 0.0003942281274979293, 'epoch': 0.09}
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{'loss': 1.7347, 'learning_rate': 0.0003942056687124506, 'epoch': 0.09}
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{'loss': 1.7033, 'learning_rate': 0.0003941831669596037, 'epoch': 0.09}
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{'loss': 1.9121, 'learning_rate': 0.0003941606222443671, 'epoch': 0.09}
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{'loss': 1.7977, 'learning_rate': 0.0003941380345717287, 'epoch': 0.09}
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{'loss': 1.8368, 'learning_rate': 0.000394115403946686, 'epoch': 0.09}
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{'loss': 1.7594, 'learning_rate': 0.000394092730374246, 'epoch': 0.09}
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{'loss': 1.881, 'learning_rate': 0.00039407001385942505, 'epoch': 0.09}
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{'loss': 1.6392, 'learning_rate': 0.0003940472544072491, 'epoch': 0.09}
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{'loss': 1.8244, 'learning_rate': 0.00039402445202275373, 'epoch': 0.09}
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{'loss': 1.9341, 'learning_rate': 0.00039400160671098375, 'epoch': 0.09}
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{'loss': 1.5803, 'learning_rate': 0.0003939787184769937, 'epoch': 0.09}
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{'loss': 1.9318, 'learning_rate': 0.0003939557873258475, 'epoch': 0.09}
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{'loss': 1.7603, 'learning_rate': 0.00039393281326261854, 'epoch': 0.09}
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{'loss': 1.7598, 'learning_rate': 0.0003939097962923899, 'epoch': 0.09}
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{'loss': 1.898, 'learning_rate': 0.00039388673642025385, 'epoch': 0.09}
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{'loss': 1.603, 'learning_rate': 0.0003938636336513124, 'epoch': 0.09}
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{'loss': 1.7666, 'learning_rate': 0.0003938404879906769, 'epoch': 0.09}
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{'loss': 1.7157, 'learning_rate': 0.00039381729944346837, 'epoch': 0.09}
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{'loss': 1.6146, 'learning_rate': 0.00039379406801481713, 'epoch': 0.09}
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+  warnings.warn(
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{'loss': 1.7353, 'learning_rate': 0.00032756596352814457, 'epoch': 0.29}
+
 29%|██▉       | 1969/6779 [1:13:01<3:01:21,  2.26s/it]
 29%|██▉       | 1970/6779 [1:13:03<2:57:14,  2.21s/it]
                                                       
{'loss': 1.7075, 'learning_rate': 0.0003274934959544434, 'epoch': 0.29}
+
 29%|██▉       | 1970/6779 [1:13:03<2:57:14,  2.21s/it]
 29%|██▉       | 1971/6779 [1:13:05<2:55:15,  2.19s/it]
                                                       
{'loss': 1.7154, 'learning_rate': 0.00032742100017322395, 'epoch': 0.29}
+
 29%|██▉       | 1971/6779 [1:13:05<2:55:15,  2.19s/it]
 29%|██▉       | 1972/6779 [1:13:07<2:55:00,  2.18s/it]
                                                       
{'loss': 1.647, 'learning_rate': 0.00032734847620052545, 'epoch': 0.29}
+
 29%|██▉       | 1972/6779 [1:13:07<2:55:00,  2.18s/it]
 29%|██▉       | 1973/6779 [1:13:09<2:52:39,  2.16s/it]
                                                       
{'loss': 1.7006, 'learning_rate': 0.0003272759240523937, 'epoch': 0.29}
+
 29%|██▉       | 1973/6779 [1:13:09<2:52:39,  2.16s/it]
 29%|██▉       | 1974/6779 [1:13:12<2:52:36,  2.16s/it]
                                                       
{'loss': 1.8209, 'learning_rate': 0.0003272033437448806, 'epoch': 0.29}
+
 29%|██▉       | 1974/6779 [1:13:12<2:52:36,  2.16s/it]
 29%|██▉       | 1975/6779 [1:13:14<2:49:39,  2.12s/it]
                                                       
{'loss': 1.6779, 'learning_rate': 0.0003271307352940443, 'epoch': 0.29}
+
 29%|██▉       | 1975/6779 [1:13:14<2:49:39,  2.12s/it]
 29%|██▉       | 1976/6779 [1:13:16<2:53:33,  2.17s/it]
                                                       
{'loss': 1.7442, 'learning_rate': 0.0003270580987159492, 'epoch': 0.29}
+
 29%|██▉       | 1976/6779 [1:13:16<2:53:33,  2.17s/it]
 29%|██▉       | 1977/6779 [1:13:18<2:56:21,  2.20s/it]
                                                       
{'loss': 1.6925, 'learning_rate': 0.0003269854340266659, 'epoch': 0.29}
+
 29%|██▉       | 1977/6779 [1:13:18<2:56:21,  2.20s/it]
 29%|██▉       | 1978/6779 [1:13:20<2:54:14,  2.18s/it]
                                                       
{'loss': 1.8078, 'learning_rate': 0.00032691274124227123, 'epoch': 0.29}
+
 29%|██▉       | 1978/6779 [1:13:20<2:54:14,  2.18s/it]
 29%|██▉       | 1979/6779 [1:13:23<2:55:07,  2.19s/it]
                                                       
{'loss': 1.8137, 'learning_rate': 0.0003268400203788482, 'epoch': 0.29}
+
 29%|██▉       | 1979/6779 [1:13:23<2:55:07,  2.19s/it]
 29%|██▉       | 1980/6779 [1:13:25<2:58:15,  2.23s/it]
                                                       
{'loss': 1.8213, 'learning_rate': 0.0003267672714524861, 'epoch': 0.29}
+
 29%|██▉       | 1980/6779 [1:13:25<2:58:15,  2.23s/it]
 29%|██▉       | 1981/6779 [1:13:27<3:01:57,  2.28s/it]
                                                       
{'loss': 1.8623, 'learning_rate': 0.0003266944944792803, 'epoch': 0.29}
+
 29%|██▉       | 1981/6779 [1:13:27<3:01:57,  2.28s/it]
 29%|██▉       | 1982/6779 [1:13:29<2:59:36,  2.25s/it]
                                                       
{'loss': 1.7186, 'learning_rate': 0.00032662168947533265, 'epoch': 0.29}
+
 29%|██▉       | 1982/6779 [1:13:29<2:59:36,  2.25s/it]
 29%|██▉       | 1983/6779 [1:13:32<2:59:45,  2.25s/it]
                                                       
{'loss': 1.8255, 'learning_rate': 0.00032654885645675086, 'epoch': 0.29}
+
 29%|██▉       | 1983/6779 [1:13:32<2:59:45,  2.25s/it]
 29%|██▉       | 1984/6779 [1:13:34<2:54:55,  2.19s/it]
                                                       
{'loss': 1.673, 'learning_rate': 0.0003264759954396491, 'epoch': 0.29}
+
 29%|██▉       | 1984/6779 [1:13:34<2:54:55,  2.19s/it]
 29%|██▉       | 1985/6779 [1:13:36<2:52:11,  2.16s/it]
                                                       
{'loss': 1.6989, 'learning_rate': 0.0003264031064401475, 'epoch': 0.29}
+
 29%|██▉       | 1985/6779 [1:13:36<2:52:11,  2.16s/it]
 29%|██▉       | 1986/6779 [1:13:38<2:49:09,  2.12s/it]
                                                       
{'loss': 1.7535, 'learning_rate': 0.00032633018947437266, 'epoch': 0.29}
+
 29%|██▉       | 1986/6779 [1:13:38<2:49:09,  2.12s/it]
 29%|██▉       | 1987/6779 [1:13:40<2:47:09,  2.09s/it]
                                                       
{'loss': 1.8201, 'learning_rate': 0.0003262572445584571, 'epoch': 0.29}
+
 29%|██▉       | 1987/6779 [1:13:40<2:47:09,  2.09s/it]
 29%|██▉       | 1988/6779 [1:13:42<2:49:04,  2.12s/it]
                                                       
{'loss': 1.7521, 'learning_rate': 0.0003261842717085397, 'epoch': 0.29}
+
 29%|██▉       | 1988/6779 [1:13:42<2:49:04,  2.12s/it]
 29%|██▉       | 1989/6779 [1:13:45<3:00:48,  2.26s/it]
                                                       
{'loss': 1.7498, 'learning_rate': 0.0003261112709407655, 'epoch': 0.29}
+
 29%|██▉       | 1989/6779 [1:13:45<3:00:48,  2.26s/it]
 29%|██▉       | 1990/6779 [1:13:47<2:59:05,  2.24s/it]
                                                       
{'loss': 1.6727, 'learning_rate': 0.00032603824227128556, 'epoch': 0.29}
+
 29%|██▉       | 1990/6779 [1:13:47<2:59:05,  2.24s/it]
 29%|██▉       | 1991/6779 [1:13:49<2:58:08,  2.23s/it]
                                                       
{'loss': 1.9731, 'learning_rate': 0.0003259651857162574, 'epoch': 0.29}
+
 29%|██▉       | 1991/6779 [1:13:49<2:58:08,  2.23s/it]
 29%|██▉       | 1992/6779 [1:13:51<2:54:46,  2.19s/it]
                                                       
{'loss': 1.8877, 'learning_rate': 0.0003258921012918444, 'epoch': 0.29}
+
 29%|██▉       | 1992/6779 [1:13:51<2:54:46,  2.19s/it]
 29%|██▉       | 1993/6779 [1:13:53<2:53:46,  2.18s/it]
                                                       
{'loss': 1.7571, 'learning_rate': 0.00032581898901421635, 'epoch': 0.29}
+
 29%|██▉       | 1993/6779 [1:13:53<2:53:46,  2.18s/it]
 29%|██▉       | 1994/6779 [1:13:55<2:53:21,  2.17s/it]
                                                       
{'loss': 1.7152, 'learning_rate': 0.0003257458488995491, 'epoch': 0.29}
+
 29%|██▉       | 1994/6779 [1:13:55<2:53:21,  2.17s/it]
 29%|██▉       | 1995/6779 [1:13:58<2:53:01,  2.17s/it]
                                                       
{'loss': 1.8582, 'learning_rate': 0.00032567268096402453, 'epoch': 0.29}
+
 29%|██▉       | 1995/6779 [1:13:58<2:53:01,  2.17s/it]
 29%|██▉       | 1996/6779 [1:14:00<2:53:36,  2.18s/it]
                                                       
{'loss': 1.8215, 'learning_rate': 0.00032559948522383093, 'epoch': 0.29}
+
 29%|██▉       | 1996/6779 [1:14:00<2:53:36,  2.18s/it]
 29%|██▉       | 1997/6779 [1:14:02<3:01:07,  2.27s/it]
                                                       
{'loss': 1.7961, 'learning_rate': 0.0003255262616951626, 'epoch': 0.29}
+
 29%|██▉       | 1997/6779 [1:14:02<3:01:07,  2.27s/it]
 29%|██▉       | 1998/6779 [1:14:05<3:00:21,  2.26s/it]
                                                       
{'loss': 1.7723, 'learning_rate': 0.00032545301039422, 'epoch': 0.29}
+
 29%|██▉       | 1998/6779 [1:14:05<3:00:21,  2.26s/it]
 29%|██▉       | 1999/6779 [1:14:07<2:59:42,  2.26s/it]
                                                       
{'loss': 1.8633, 'learning_rate': 0.00032537973133720964, 'epoch': 0.29}
+
 29%|██▉       | 1999/6779 [1:14:07<2:59:42,  2.26s/it]
 30%|██▉       | 2000/6779 [1:14:09<3:02:02,  2.29s/it]
                                                       
{'loss': 1.664, 'learning_rate': 0.0003253064245403445, 'epoch': 0.3}
+
 30%|██▉       | 2000/6779 [1:14:09<3:02:02,  2.29s/it]/home/aiops/duanky/miniconda3/envs/lora/lib/python3.11/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
+  warnings.warn(
+
 30%|██▉       | 2001/6779 [1:14:12<3:10:45,  2.40s/it]
                                                       
{'loss': 1.7441, 'learning_rate': 0.0003252330900198432, 'epoch': 0.3}
+
 30%|██▉       | 2001/6779 [1:14:12<3:10:45,  2.40s/it]
 30%|██▉       | 2002/6779 [1:14:14<3:05:08,  2.33s/it]
                                                       
{'loss': 1.8134, 'learning_rate': 0.00032515972779193094, 'epoch': 0.3}
+
 30%|██▉       | 2002/6779 [1:14:14<3:05:08,  2.33s/it]
 30%|██▉       | 2003/6779 [1:14:16<3:00:06,  2.26s/it]
                                                       
{'loss': 1.6695, 'learning_rate': 0.0003250863378728388, 'epoch': 0.3}
+
 30%|██▉       | 2003/6779 [1:14:16<3:00:06,  2.26s/it]
 30%|██▉       | 2004/6779 [1:14:18<3:01:09,  2.28s/it]
                                                       
{'loss': 1.6399, 'learning_rate': 0.00032501292027880413, 'epoch': 0.3}
+
 30%|██▉       | 2004/6779 [1:14:18<3:01:09,  2.28s/it]
 30%|██▉       | 2005/6779 [1:14:21<3:01:02,  2.28s/it]
                                                       
{'loss': 1.7118, 'learning_rate': 0.0003249394750260703, 'epoch': 0.3}
+
 30%|██▉       | 2005/6779 [1:14:21<3:01:02,  2.28s/it]
 30%|██▉       | 2006/6779 [1:14:23<3:01:54,  2.29s/it]
                                                       
{'loss': 1.6273, 'learning_rate': 0.00032486600213088677, 'epoch': 0.3}
+
 30%|██▉       | 2006/6779 [1:14:23<3:01:54,  2.29s/it]
 30%|██▉       | 2007/6779 [1:14:25<2:58:56,  2.25s/it]
                                                       
{'loss': 1.8432, 'learning_rate': 0.00032479250160950926, 'epoch': 0.3}
+
 30%|██▉       | 2007/6779 [1:14:25<2:58:56,  2.25s/it]
 30%|██▉       | 2008/6779 [1:14:27<2:55:41,  2.21s/it]
                                                       
{'loss': 1.6697, 'learning_rate': 0.00032471897347819946, 'epoch': 0.3}
+
 30%|██▉       | 2008/6779 [1:14:27<2:55:41,  2.21s/it]
 30%|██▉       | 2009/6779 [1:14:31<3:25:02,  2.58s/it]
                                                       
{'loss': 1.7412, 'learning_rate': 0.0003246454177532253, 'epoch': 0.3}
+
 30%|██▉       | 2009/6779 [1:14:31<3:25:02,  2.58s/it]
 30%|██▉       | 2010/6779 [1:14:33<3:14:47,  2.45s/it]
                                                       
{'loss': 1.5673, 'learning_rate': 0.00032457183445086063, 'epoch': 0.3}
+
 30%|██▉       | 2010/6779 [1:14:33<3:14:47,  2.45s/it]
 30%|██▉       | 2011/6779 [1:14:35<3:05:55,  2.34s/it]
                                                       
{'loss': 1.5494, 'learning_rate': 0.0003244982235873856, 'epoch': 0.3}
+
 30%|██▉       | 2011/6779 [1:14:35<3:05:55,  2.34s/it]
 30%|██▉       | 2012/6779 [1:14:37<2:59:52,  2.26s/it]
                                                       
{'loss': 1.8153, 'learning_rate': 0.0003244245851790864, 'epoch': 0.3}
+
 30%|██▉       | 2012/6779 [1:14:37<2:59:52,  2.26s/it]
 30%|██▉       | 2013/6779 [1:14:39<2:52:59,  2.18s/it]
                                                       
{'loss': 1.7135, 'learning_rate': 0.0003243509192422551, 'epoch': 0.3}
+
 30%|██▉       | 2013/6779 [1:14:39<2:52:59,  2.18s/it]
 30%|██▉       | 2014/6779 [1:14:41<2:52:27,  2.17s/it]
                                                       
{'loss': 1.7113, 'learning_rate': 0.0003242772257931904, 'epoch': 0.3}
+
 30%|██▉       | 2014/6779 [1:14:41<2:52:27,  2.17s/it]
 30%|██▉       | 2015/6779 [1:14:43<2:54:57,  2.20s/it]
                                                       
{'loss': 1.8381, 'learning_rate': 0.0003242035048481964, 'epoch': 0.3}
+
 30%|██▉       | 2015/6779 [1:14:43<2:54:57,  2.20s/it]
 30%|██▉       | 2016/6779 [1:14:46<2:54:46,  2.20s/it]
                                                       
{'loss': 1.7193, 'learning_rate': 0.00032412975642358375, 'epoch': 0.3}
+
 30%|██▉       | 2016/6779 [1:14:46<2:54:46,  2.20s/it]
 30%|██▉       | 2017/6779 [1:14:48<2:53:11,  2.18s/it]
                                                       
{'loss': 1.7164, 'learning_rate': 0.000324055980535669, 'epoch': 0.3}
+
 30%|██▉       | 2017/6779 [1:14:48<2:53:11,  2.18s/it]
 30%|██▉       | 2018/6779 [1:14:50<2:53:17,  2.18s/it]
                                                       
{'loss': 1.6114, 'learning_rate': 0.00032398217720077494, 'epoch': 0.3}
+
 30%|██▉       | 2018/6779 [1:14:50<2:53:17,  2.18s/it]
 30%|██▉       | 2019/6779 [1:14:52<2:52:55,  2.18s/it]
                                                       
{'loss': 1.6986, 'learning_rate': 0.00032390834643523025, 'epoch': 0.3}
+
 30%|██▉       | 2019/6779 [1:14:52<2:52:55,  2.18s/it]
 30%|██▉       | 2020/6779 [1:14:54<2:49:45,  2.14s/it]
                                                       
{'loss': 1.7609, 'learning_rate': 0.0003238344882553697, 'epoch': 0.3}
+
 30%|██▉       | 2020/6779 [1:14:54<2:49:45,  2.14s/it]
 30%|██▉       | 2021/6779 [1:14:56<2:51:21,  2.16s/it]
                                                       
{'loss': 1.6817, 'learning_rate': 0.0003237606026775341, 'epoch': 0.3}
+
 30%|██▉       | 2021/6779 [1:14:56<2:51:21,  2.16s/it]
 30%|██▉       | 2022/6779 [1:14:59<2:53:40,  2.19s/it]
                                                       
{'loss': 1.6873, 'learning_rate': 0.0003236866897180706, 'epoch': 0.3}
+
 30%|██▉       | 2022/6779 [1:14:59<2:53:40,  2.19s/it]
 30%|██▉       | 2023/6779 [1:15:01<2:58:34,  2.25s/it]
                                                       
{'loss': 1.7534, 'learning_rate': 0.0003236127493933321, 'epoch': 0.3}
+
 30%|██▉       | 2023/6779 [1:15:01<2:58:34,  2.25s/it]
 30%|██▉       | 2024/6779 [1:15:03<2:58:48,  2.26s/it]
                                                       
{'loss': 1.8136, 'learning_rate': 0.0003235387817196776, 'epoch': 0.3}
+
 30%|██▉       | 2024/6779 [1:15:03<2:58:48,  2.26s/it]
 30%|██▉       | 2025/6779 [1:15:06<2:59:14,  2.26s/it]
                                                       
{'loss': 1.7058, 'learning_rate': 0.0003234647867134723, 'epoch': 0.3}
+
 30%|██▉       | 2025/6779 [1:15:06<2:59:14,  2.26s/it]
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{'loss': 1.8149, 'learning_rate': 0.00032339076439108727, 'epoch': 0.3}
+
 30%|██▉       | 2026/6779 [1:15:08<2:54:25,  2.20s/it]
 30%|██▉       | 2027/6779 [1:15:10<2:50:11,  2.15s/it]
                                                       
{'loss': 1.8045, 'learning_rate': 0.00032331671476889975, 'epoch': 0.3}
+
 30%|██▉       | 2027/6779 [1:15:10<2:50:11,  2.15s/it]
 30%|██▉       | 2028/6779 [1:15:12<2:52:33,  2.18s/it]
                                                       
{'loss': 1.7454, 'learning_rate': 0.000323242637863293, 'epoch': 0.3}
+
 30%|██▉       | 2028/6779 [1:15:12<2:52:33,  2.18s/it]
 30%|██▉       | 2029/6779 [1:15:14<2:55:15,  2.21s/it]
                                                       
{'loss': 1.7279, 'learning_rate': 0.00032316853369065626, 'epoch': 0.3}
+
 30%|██▉       | 2029/6779 [1:15:14<2:55:15,  2.21s/it]
 30%|██▉       | 2030/6779 [1:15:16<2:57:21,  2.24s/it]
                                                       
{'loss': 1.6452, 'learning_rate': 0.0003230944022673848, 'epoch': 0.3}
+
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{'loss': 1.7889, 'learning_rate': 0.00032302024360988, 'epoch': 0.3}
+
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{'loss': 1.9362, 'learning_rate': 0.0003229460577345493, 'epoch': 0.3}
+
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{'loss': 1.7183, 'learning_rate': 0.0003228718446578059, 'epoch': 0.3}
+
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{'loss': 1.7026, 'learning_rate': 0.0003227976043960693, 'epoch': 0.3}
+
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{'loss': 1.7087, 'learning_rate': 0.00032272333696576494, 'epoch': 0.3}
+
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{'loss': 1.7274, 'learning_rate': 0.0003226490423833242, 'epoch': 0.3}
+
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{'loss': 1.9432, 'learning_rate': 0.00032257472066518454, 'epoch': 0.3}
+
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{'loss': 1.8579, 'learning_rate': 0.0003225003718277894, 'epoch': 0.3}
+
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{'loss': 1.6696, 'learning_rate': 0.0003224259958875882, 'epoch': 0.3}
+
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{'loss': 1.7382, 'learning_rate': 0.0002442683154204064, 'epoch': 0.44}
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{'loss': 1.7442, 'learning_rate': 0.00024298299968914972, 'epoch': 0.44}
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{'loss': 1.867, 'learning_rate': 0.0002428911194383804, 'epoch': 0.44}
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{'loss': 1.9693, 'learning_rate': 0.0002427073304886129, 'epoch': 0.44}
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{'loss': 1.6912, 'learning_rate': 0.0002426154218302775, 'epoch': 0.44}
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{'loss': 1.652, 'learning_rate': 0.00024243157624837566, 'epoch': 0.44}
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{'loss': 1.7776, 'learning_rate': 0.00024233963936548452, 'epoch': 0.44}
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{'loss': 1.8523, 'learning_rate': 0.00024233963936548452, 'epoch': 0.44}
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{'loss': 1.5334, 'learning_rate': 0.00024206377259314513, 'epoch': 0.44}
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{'loss': 1.7405, 'learning_rate': 0.0002417878220625708, 'epoch': 0.44}
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{'loss': 1.8009, 'learning_rate': 0.00024169582003440504, 'epoch': 0.44}
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{'loss': 1.5976, 'learning_rate': 0.0002416038087811757, 'epoch': 0.44}
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{'loss': 1.7503, 'learning_rate': 0.00024151178832323983, 'epoch': 0.44}
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{'loss': 1.6757, 'learning_rate': 0.00024141975868095678, 'epoch': 0.44}
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{'loss': 1.7599, 'learning_rate': 0.00024132771987468786, 'epoch': 0.44}
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{'loss': 1.8226, 'learning_rate': 0.0002412356719247962, 'epoch': 0.44}
+
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+  warnings.warn(
+
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{'loss': 1.6389, 'learning_rate': 0.00024114361485164722, 'epoch': 0.44}
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{'loss': 1.7827, 'learning_rate': 0.00024040683227369116, 'epoch': 0.44}
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{'loss': 1.71, 'learning_rate': 0.00024013039073851182, 'epoch': 0.44}
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+  warnings.warn(
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+  warnings.warn(
+
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{'loss': 1.6, 'learning_rate': 1.4166858257814896e-05, 'epoch': 0.88}
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{'loss': 1.6729, 'learning_rate': 1.4132103189644885e-05, 'epoch': 0.88}
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{'loss': 1.6283, 'learning_rate': 1.4097389244138348e-05, 'epoch': 0.88}
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{'loss': 1.6897, 'learning_rate': 1.4062716428975542e-05, 'epoch': 0.88}
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{'loss': 1.6414, 'learning_rate': 1.4028084751827775e-05, 'epoch': 0.88}
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{'loss': 1.682, 'learning_rate': 1.399349422035714e-05, 'epoch': 0.88}
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{'loss': 1.4992, 'learning_rate': 1.3958944842216758e-05, 'epoch': 0.88}
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{'loss': 1.8063, 'learning_rate': 1.3924436625050452e-05, 'epoch': 0.88}
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{'loss': 1.5491, 'learning_rate': 1.3889969576493134e-05, 'epoch': 0.88}
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{'loss': 1.7913, 'learning_rate': 1.3855543704170526e-05, 'epoch': 0.88}
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{'loss': 1.5953, 'learning_rate': 1.3821159015699182e-05, 'epoch': 0.88}
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{'loss': 1.6822, 'learning_rate': 1.3786815518686679e-05, 'epoch': 0.88}
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{'loss': 1.5187, 'learning_rate': 1.3718252129422481e-05, 'epoch': 0.88}
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{'loss': 1.7299, 'learning_rate': 1.3684032252340184e-05, 'epoch': 0.88}
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{'loss': 1.6522, 'learning_rate': 1.3615716171130533e-05, 'epoch': 0.88}
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{'loss': 1.7511, 'learning_rate': 1.3581619982117822e-05, 'epoch': 0.88}
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{'loss': 1.7496, 'learning_rate': 1.354756503756116e-05, 'epoch': 0.88}
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{'loss': 1.6538, 'learning_rate': 1.3513551344995057e-05, 'epoch': 0.88}
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{'loss': 1.5835, 'learning_rate': 1.3479578911944979e-05, 'epoch': 0.88}
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{'loss': 1.6213, 'learning_rate': 1.3445647745927136e-05, 'epoch': 0.88}
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{'loss': 1.6461, 'learning_rate': 1.3411757854448726e-05, 'epoch': 0.88}
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{'loss': 1.4926, 'learning_rate': 1.337790924500779e-05, 'epoch': 0.89}
+
 89%|████████▊ | 6000/6779 [3:42:45<29:18,  2.26s/it]/home/aiops/duanky/miniconda3/envs/lora/lib/python3.11/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
+  warnings.warn(
+
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{'loss': 1.6328, 'learning_rate': 1.3344101925093255e-05, 'epoch': 0.89}
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{'loss': 1.4972, 'learning_rate': 1.3310335902184822e-05, 'epoch': 0.89}
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{'loss': 1.6236, 'learning_rate': 1.3276611183753118e-05, 'epoch': 0.89}
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{'loss': 1.5541, 'learning_rate': 1.3242927777259662e-05, 'epoch': 0.89}
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{'loss': 1.5283, 'learning_rate': 1.3209285690156736e-05, 'epoch': 0.89}
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{'loss': 1.7916, 'learning_rate': 1.3175684929887589e-05, 'epoch': 0.89}
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{'loss': 1.5063, 'learning_rate': 1.314212550388627e-05, 'epoch': 0.89}
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{'loss': 1.5822, 'learning_rate': 1.3108607419577734e-05, 'epoch': 0.89}
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{'loss': 1.588, 'learning_rate': 1.3075130684377646e-05, 'epoch': 0.89}
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{'loss': 1.5325, 'learning_rate': 1.3041695305692748e-05, 'epoch': 0.89}
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{'loss': 1.773, 'learning_rate': 1.3008301290920411e-05, 'epoch': 0.89}
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{'loss': 1.643, 'learning_rate': 1.297494864744897e-05, 'epoch': 0.89}
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{'loss': 1.6097, 'learning_rate': 1.2941637382657613e-05, 'epoch': 0.89}
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{'loss': 1.8713, 'learning_rate': 1.2908367503916329e-05, 'epoch': 0.89}
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{'loss': 1.5358, 'learning_rate': 1.2875139018585991e-05, 'epoch': 0.89}
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{'loss': 1.5877, 'learning_rate': 1.284195193401827e-05, 'epoch': 0.89}
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{'loss': 1.6115, 'learning_rate': 1.280880625755574e-05, 'epoch': 0.89}
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{'loss': 1.4446, 'learning_rate': 1.277570199653173e-05, 'epoch': 0.89}
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{'loss': 1.5922, 'learning_rate': 1.2742639158270431e-05, 'epoch': 0.89}
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{'loss': 1.6521, 'learning_rate': 1.2709617750086922e-05, 'epoch': 0.89}
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{'loss': 1.7812, 'learning_rate': 1.2676637779287092e-05, 'epoch': 0.89}
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{'loss': 1.3578, 'learning_rate': 1.2643699253167663e-05, 'epoch': 0.89}
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{'loss': 1.6594, 'learning_rate': 1.2610802179016112e-05, 'epoch': 0.89}
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{'loss': 1.5944, 'learning_rate': 1.2545132415721106e-05, 'epoch': 0.89}
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{'loss': 1.6182, 'learning_rate': 1.2512359741106871e-05, 'epoch': 0.89}
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{'loss': 1.5774, 'learning_rate': 1.2479628547518941e-05, 'epoch': 0.89}
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{'loss': 1.6514, 'learning_rate': 1.2414290632379711e-05, 'epoch': 0.89}
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{'loss': 1.735, 'learning_rate': 1.2349118728126563e-05, 'epoch': 0.89}
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{'loss': 1.6001, 'learning_rate': 1.2284112892435829e-05, 'epoch': 0.89}
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{'train_runtime': 15107.5523, 'train_samples_per_second': 14.359, 'train_steps_per_second': 0.449, 'train_loss': 1.7056976145990375, 'epoch': 1.0}
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+wandb: 
+wandb: Run history:
+wandb:                    train/epoch ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▄▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇████
+wandb:              train/global_step ▁▁▁▂▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███
+wandb:            train/learning_rate ▅███████▇▇▇▇▇▆▆▆▆▅▅▅▄▄▄▄▃▃▃▃▂▂▂▂▂▁▁▁▁▁▁▁
+wandb:                     train/loss ▇█▅▄▄▅▆█▆▄▅▅▆▄▅▅▅▆▄▇▅▅▄▅▃▆▃▄▄▆▇▃▃▄▁▃▃▃▃▃
+wandb:               train/total_flos ▁
+wandb:               train/train_loss ▁
+wandb:            train/train_runtime ▁
+wandb: train/train_samples_per_second ▁
+wandb:   train/train_steps_per_second ▁
+wandb: 
+wandb: Run summary:
+wandb:                    train/epoch 1.0
+wandb:              train/global_step 6779
+wandb:            train/learning_rate 0.0
+wandb:                     train/loss 1.7514
+wandb:               train/total_flos 1.5507444499386204e+18
+wandb:               train/train_loss 1.7057
+wandb:            train/train_runtime 15107.5523
+wandb: train/train_samples_per_second 14.359
+wandb:   train/train_steps_per_second 0.449
+wandb: 
+wandb: 🚀 View run belle_dolphine-p12 at: https://wandb.ai/nus_keyu/lora-moe/runs/39wnh4vr
+wandb: Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
+wandb: Find logs at: ./wandb/run-20231229_074425-39wnh4vr/logs