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--- |
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license: apache-2.0 |
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base_model: mistralai/Mistral-7B-Instruct-v0.2 |
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tags: |
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- trl |
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- dpo |
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- generated_from_trainer |
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model-index: |
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- name: mistralit2_1000_STEPS_1e8_rate_0.1_beta_DPO |
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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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# mistralit2_1000_STEPS_1e8_rate_0.1_beta_DPO |
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This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6920 |
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- Rewards/chosen: -0.0058 |
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- Rewards/rejected: -0.0082 |
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- Rewards/accuracies: 0.5121 |
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- Rewards/margins: 0.0024 |
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- Logps/rejected: -28.6543 |
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- Logps/chosen: -23.4436 |
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- Logits/rejected: -2.8649 |
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- Logits/chosen: -2.8652 |
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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: 1e-08 |
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- train_batch_size: 4 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 100 |
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- training_steps: 1000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |
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|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| |
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| 0.693 | 0.1 | 50 | 0.6928 | 0.0007 | -0.0000 | 0.4549 | 0.0007 | -28.5728 | -23.3792 | -2.8652 | -2.8654 | |
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| 0.693 | 0.2 | 100 | 0.6920 | 0.0012 | -0.0011 | 0.4945 | 0.0023 | -28.5838 | -23.3741 | -2.8653 | -2.8655 | |
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| 0.693 | 0.29 | 150 | 0.6923 | -0.0015 | -0.0033 | 0.4989 | 0.0018 | -28.6052 | -23.4006 | -2.8651 | -2.8653 | |
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| 0.694 | 0.39 | 200 | 0.6923 | -0.0020 | -0.0037 | 0.4813 | 0.0017 | -28.6093 | -23.4058 | -2.8651 | -2.8653 | |
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| 0.6916 | 0.49 | 250 | 0.6922 | -0.0026 | -0.0046 | 0.4879 | 0.0021 | -28.6189 | -23.4118 | -2.8651 | -2.8654 | |
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| 0.6927 | 0.59 | 300 | 0.6920 | -0.0039 | -0.0063 | 0.5011 | 0.0023 | -28.6350 | -23.4253 | -2.8650 | -2.8653 | |
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| 0.6941 | 0.68 | 350 | 0.6927 | -0.0048 | -0.0058 | 0.4659 | 0.0010 | -28.6304 | -23.4334 | -2.8650 | -2.8652 | |
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| 0.6924 | 0.78 | 400 | 0.6922 | -0.0049 | -0.0068 | 0.4989 | 0.0019 | -28.6399 | -23.4345 | -2.8650 | -2.8653 | |
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| 0.6919 | 0.88 | 450 | 0.6918 | -0.0056 | -0.0084 | 0.4857 | 0.0028 | -28.6562 | -23.4418 | -2.8650 | -2.8653 | |
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| 0.6913 | 0.98 | 500 | 0.6913 | -0.0047 | -0.0085 | 0.5077 | 0.0038 | -28.6577 | -23.4328 | -2.8649 | -2.8652 | |
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| 0.6914 | 1.07 | 550 | 0.6915 | -0.0034 | -0.0067 | 0.5143 | 0.0033 | -28.6398 | -23.4200 | -2.8650 | -2.8653 | |
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| 0.6939 | 1.17 | 600 | 0.6922 | -0.0069 | -0.0089 | 0.5033 | 0.0020 | -28.6613 | -23.4550 | -2.8650 | -2.8652 | |
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| 0.6917 | 1.27 | 650 | 0.6920 | -0.0056 | -0.0081 | 0.5231 | 0.0025 | -28.6535 | -23.4422 | -2.8650 | -2.8653 | |
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| 0.6919 | 1.37 | 700 | 0.6921 | -0.0052 | -0.0074 | 0.5055 | 0.0021 | -28.6463 | -23.4383 | -2.8650 | -2.8653 | |
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| 0.6929 | 1.46 | 750 | 0.6915 | -0.0044 | -0.0078 | 0.5363 | 0.0034 | -28.6506 | -23.4298 | -2.8650 | -2.8653 | |
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| 0.6919 | 1.56 | 800 | 0.6922 | -0.0063 | -0.0083 | 0.5209 | 0.0020 | -28.6553 | -23.4489 | -2.8649 | -2.8652 | |
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| 0.6925 | 1.66 | 850 | 0.6921 | -0.0058 | -0.0080 | 0.5121 | 0.0022 | -28.6528 | -23.4438 | -2.8649 | -2.8652 | |
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| 0.6925 | 1.76 | 900 | 0.6920 | -0.0058 | -0.0082 | 0.5121 | 0.0024 | -28.6543 | -23.4436 | -2.8649 | -2.8652 | |
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| 0.6939 | 1.86 | 950 | 0.6920 | -0.0058 | -0.0082 | 0.5121 | 0.0024 | -28.6543 | -23.4436 | -2.8649 | -2.8652 | |
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| 0.6924 | 1.95 | 1000 | 0.6920 | -0.0058 | -0.0082 | 0.5121 | 0.0024 | -28.6543 | -23.4436 | -2.8649 | -2.8652 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.0.0+cu117 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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