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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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datasets: |
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- truthful_qa |
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metrics: |
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- accuracy |
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model-index: |
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- name: vicuna_mc_finetune |
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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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# vicuna_mc_finetune |
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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 the truthful_qa dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8867 |
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- Accuracy: 0.2378 |
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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: 6 |
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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 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 1.7307 | 1.0 | 109 | 1.5327 | 0.4024 | |
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| 1.4519 | 2.0 | 218 | 1.2341 | 0.7073 | |
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| 0.0207 | 3.0 | 327 | 2.2924 | 0.6280 | |
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| 1.5647 | 4.0 | 436 | 1.9344 | 0.2256 | |
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| 2.2047 | 5.0 | 545 | 1.9401 | 0.2256 | |
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| 2.016 | 6.0 | 654 | 1.8888 | 0.2256 | |
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| 1.625 | 7.0 | 763 | 1.9068 | 0.1768 | |
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| 2.0002 | 8.0 | 872 | 1.8909 | 0.1951 | |
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| 1.7906 | 9.0 | 981 | 1.8828 | 0.2195 | |
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| 1.5295 | 10.0 | 1090 | 1.8967 | 0.2195 | |
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| 1.7018 | 11.0 | 1199 | 1.8845 | 0.2378 | |
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| 1.8412 | 12.0 | 1308 | 1.8808 | 0.2073 | |
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| 2.4396 | 13.0 | 1417 | 1.8816 | 0.2012 | |
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| 1.8643 | 14.0 | 1526 | 1.8827 | 0.2012 | |
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| 1.7271 | 15.0 | 1635 | 1.8844 | 0.2256 | |
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| 1.851 | 16.0 | 1744 | 1.8720 | 0.2134 | |
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| 1.7633 | 17.0 | 1853 | 1.8786 | 0.2134 | |
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| 2.6586 | 18.0 | 1962 | 1.8723 | 0.25 | |
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| 2.0078 | 19.0 | 2071 | 1.8770 | 0.2439 | |
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| 1.4072 | 20.0 | 2180 | 1.8867 | 0.2378 | |
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### Framework versions |
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- Transformers 4.36.0.dev0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.13.1 |
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- Tokenizers 0.14.1 |
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