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--- |
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license: llama2 |
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base_model: lmsys/vicuna-7b-v1.5 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: finetune_arc_20_cot |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# finetune_arc_20_cot |
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This model is a fine-tuned version of [lmsys/vicuna-7b-v1.5](https://huggingface.co/lmsys/vicuna-7b-v1.5) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.8229 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 5 |
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- num_epochs: 20 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.2708 | 1.0 | 150 | 1.2201 | |
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| 0.8854 | 2.0 | 300 | 1.2765 | |
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| 0.567 | 3.0 | 450 | 1.4685 | |
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| 0.3112 | 4.0 | 600 | 1.7395 | |
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| 0.1762 | 5.0 | 750 | 2.0026 | |
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| 0.1228 | 6.0 | 900 | 2.0326 | |
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| 0.1002 | 7.0 | 1050 | 2.1066 | |
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| 0.0931 | 8.0 | 1200 | 2.1262 | |
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| 0.1434 | 9.0 | 1350 | 2.2417 | |
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| 0.0746 | 10.0 | 1500 | 2.3327 | |
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| 0.069 | 11.0 | 1650 | 2.3327 | |
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| 0.0804 | 12.0 | 1800 | 2.5652 | |
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| 0.0586 | 13.0 | 1950 | 2.4866 | |
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| 0.0652 | 14.0 | 2100 | 2.5962 | |
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| 0.0471 | 15.0 | 2250 | 2.6461 | |
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| 0.054 | 16.0 | 2400 | 2.6890 | |
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| 0.0602 | 17.0 | 2550 | 2.7081 | |
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| 0.0562 | 18.0 | 2700 | 2.7800 | |
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| 0.064 | 19.0 | 2850 | 2.8103 | |
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| 0.0509 | 20.0 | 3000 | 2.8229 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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