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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_race_20 |
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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_race_20 |
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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: 3.4669 |
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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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| 1.2823 | 1.0 | 150 | 1.4463 | |
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| 0.7207 | 2.0 | 300 | 1.5249 | |
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| 0.4983 | 3.0 | 450 | 1.6580 | |
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| 0.5956 | 4.0 | 600 | 1.8347 | |
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| 0.1806 | 5.0 | 750 | 2.0078 | |
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| 0.1439 | 6.0 | 900 | 2.2482 | |
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| 0.1399 | 7.0 | 1050 | 2.3858 | |
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| 0.0826 | 8.0 | 1200 | 2.4455 | |
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| 0.0878 | 9.0 | 1350 | 2.5889 | |
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| 0.0564 | 10.0 | 1500 | 2.7918 | |
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| 0.0641 | 11.0 | 1650 | 2.7968 | |
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| 0.0522 | 12.0 | 1800 | 2.7144 | |
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| 0.0491 | 13.0 | 1950 | 2.9539 | |
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| 0.0436 | 14.0 | 2100 | 2.9602 | |
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| 0.0431 | 15.0 | 2250 | 3.1613 | |
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| 0.0449 | 16.0 | 2400 | 3.2197 | |
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| 0.0516 | 17.0 | 2550 | 3.3331 | |
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| 0.0432 | 18.0 | 2700 | 3.4157 | |
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| 0.0448 | 19.0 | 2850 | 3.4384 | |
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| 0.0416 | 20.0 | 3000 | 3.4669 | |
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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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