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--- |
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license: apache-2.0 |
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base_model: mistralai/Mistral-7B-v0.1 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: Mistral-7B-v0.1-gen-dpo-10k |
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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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# Mistral-7B-v0.1-gen-dpo-10k |
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This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4841 |
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- Rewards/real: 6.6281 |
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- Rewards/generated: 0.7385 |
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- Rewards/accuracies: 0.9038 |
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- Rewards/margins: 5.8896 |
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- Logps/generated: -226.3850 |
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- Logps/real: -146.0557 |
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- Logits/generated: -2.4268 |
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- Logits/real: -2.5712 |
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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: 5e-07 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 16 |
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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_ratio: 0.1 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rewards/real | Rewards/generated | Rewards/accuracies | Rewards/margins | Logps/generated | Logps/real | Logits/generated | Logits/real | |
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|:-------------:|:------:|:----:|:---------------:|:------------:|:-----------------:|:------------------:|:---------------:|:---------------:|:----------:|:----------------:|:-----------:| |
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| 0.6898 | 0.1984 | 62 | 0.6845 | 0.1316 | -1.2271 | 0.8269 | 1.3587 | -246.0414 | -211.0208 | -2.6139 | -2.5606 | |
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| 0.5637 | 0.3968 | 124 | 0.6091 | 1.9039 | -1.0140 | 0.9231 | 2.9179 | -243.9099 | -193.2971 | -2.9188 | -2.9273 | |
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| 0.4765 | 0.5952 | 186 | 0.4901 | 1.6316 | -2.9131 | 0.9615 | 4.5447 | -262.9012 | -196.0205 | -2.6050 | -2.6193 | |
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| 0.4421 | 0.7936 | 248 | 0.4296 | 0.8748 | -3.7695 | 0.9423 | 4.6443 | -271.4653 | -203.5885 | -2.5477 | -2.5049 | |
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| 0.4329 | 0.992 | 310 | 0.3885 | 1.7310 | -3.2873 | 0.9808 | 5.0183 | -266.6432 | -195.0263 | -2.4849 | -2.4779 | |
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| 0.192 | 1.1904 | 372 | 0.4325 | 4.2551 | -0.5848 | 0.9231 | 4.8399 | -239.6185 | -169.7859 | -2.6992 | -2.7276 | |
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| 0.1832 | 1.3888 | 434 | 0.3965 | 4.0302 | -1.0932 | 0.9038 | 5.1234 | -244.7022 | -172.0349 | -2.6359 | -2.6597 | |
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| 0.1759 | 1.5872 | 496 | 0.4029 | 4.6281 | -1.2718 | 0.9038 | 5.8999 | -246.4886 | -166.0557 | -2.5095 | -2.5768 | |
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| 0.1911 | 1.7856 | 558 | 0.4281 | 4.7928 | -0.9888 | 0.9231 | 5.7817 | -243.6584 | -164.4082 | -2.7026 | -2.8069 | |
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| 0.1719 | 1.984 | 620 | 0.4522 | 5.4290 | 0.0713 | 0.8654 | 5.3577 | -233.0573 | -158.0468 | -2.6334 | -2.6747 | |
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| 0.1363 | 2.1824 | 682 | 0.4649 | 6.2001 | 0.9000 | 0.8846 | 5.3001 | -224.7699 | -150.3351 | -2.5111 | -2.6322 | |
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| 0.1349 | 2.3808 | 744 | 0.4958 | 6.5905 | 1.3552 | 0.8846 | 5.2353 | -220.2184 | -146.4319 | -2.5129 | -2.6396 | |
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| 0.1316 | 2.5792 | 806 | 0.4796 | 6.6882 | 1.1784 | 0.9038 | 5.5098 | -221.9857 | -145.4545 | -2.5378 | -2.6846 | |
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| 0.1293 | 2.7776 | 868 | 0.4938 | 6.8678 | 1.4561 | 0.8846 | 5.4117 | -219.2092 | -143.6585 | -2.4843 | -2.6386 | |
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| 0.1244 | 2.976 | 930 | 0.4841 | 6.6281 | 0.7385 | 0.9038 | 5.8896 | -226.3850 | -146.0557 | -2.4268 | -2.5712 | |
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### Framework versions |
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- Transformers 4.43.3 |
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- Pytorch 2.2.2+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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