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--- |
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license: apache-2.0 |
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base_model: mistralai/Mistral-7B-Instruct-v0.1 |
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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: v1_1000_STEPS_1e8_rate_01_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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# v1_1000_STEPS_1e8_rate_01_beta_DPO |
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This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6930 |
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- Rewards/chosen: -0.0000 |
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- Rewards/rejected: -0.0004 |
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- Rewards/accuracies: 0.4571 |
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- Rewards/margins: 0.0004 |
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- Logps/rejected: -16.8832 |
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- Logps/chosen: -15.2532 |
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- Logits/rejected: -3.3537 |
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- Logits/chosen: -3.3538 |
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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: 2 |
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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: 4 |
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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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| 0.6937 | 0.05 | 50 | 0.6931 | -0.0004 | -0.0006 | 0.4813 | 0.0002 | -16.8854 | -15.2569 | -3.3537 | -3.3538 | |
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| 0.6934 | 0.1 | 100 | 0.6930 | 0.0001 | -0.0003 | 0.4879 | 0.0004 | -16.8825 | -15.2519 | -3.3538 | -3.3539 | |
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| 0.6945 | 0.15 | 150 | 0.6931 | -0.0002 | -0.0003 | 0.4725 | 0.0001 | -16.8826 | -15.2550 | -3.3538 | -3.3539 | |
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| 0.6945 | 0.2 | 200 | 0.6933 | -0.0003 | -0.0000 | 0.4396 | -0.0003 | -16.8800 | -15.2561 | -3.3537 | -3.3538 | |
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| 0.693 | 0.24 | 250 | 0.6933 | -0.0002 | 0.0000 | 0.4352 | -0.0002 | -16.8791 | -15.2548 | -3.3538 | -3.3539 | |
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| 0.6934 | 0.29 | 300 | 0.6930 | 0.0003 | -0.0001 | 0.4549 | 0.0004 | -16.8806 | -15.2500 | -3.3539 | -3.3540 | |
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| 0.6945 | 0.34 | 350 | 0.6931 | -0.0007 | -0.0007 | 0.4462 | 0.0001 | -16.8867 | -15.2596 | -3.3539 | -3.3539 | |
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| 0.6914 | 0.39 | 400 | 0.6933 | -0.0006 | -0.0004 | 0.4593 | -0.0002 | -16.8834 | -15.2590 | -3.3538 | -3.3538 | |
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| 0.693 | 0.44 | 450 | 0.6932 | -0.0001 | -0.0001 | 0.4396 | -0.0000 | -16.8802 | -15.2539 | -3.3537 | -3.3537 | |
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| 0.6937 | 0.49 | 500 | 0.6931 | -0.0002 | -0.0003 | 0.4484 | 0.0001 | -16.8827 | -15.2548 | -3.3538 | -3.3539 | |
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| 0.6918 | 0.54 | 550 | 0.6930 | -0.0001 | -0.0004 | 0.4791 | 0.0003 | -16.8834 | -15.2541 | -3.3537 | -3.3538 | |
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| 0.6926 | 0.59 | 600 | 0.6933 | -0.0005 | -0.0002 | 0.4505 | -0.0002 | -16.8820 | -15.2580 | -3.3537 | -3.3537 | |
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| 0.6922 | 0.64 | 650 | 0.6933 | -0.0003 | -0.0000 | 0.4549 | -0.0003 | -16.8796 | -15.2563 | -3.3538 | -3.3539 | |
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| 0.693 | 0.68 | 700 | 0.6931 | -0.0006 | -0.0007 | 0.4484 | 0.0001 | -16.8861 | -15.2589 | -3.3538 | -3.3539 | |
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| 0.6926 | 0.73 | 750 | 0.6928 | 0.0001 | -0.0006 | 0.4879 | 0.0007 | -16.8858 | -15.2520 | -3.3538 | -3.3539 | |
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| 0.693 | 0.78 | 800 | 0.6931 | -0.0004 | -0.0007 | 0.4923 | 0.0002 | -16.8861 | -15.2574 | -3.3538 | -3.3539 | |
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| 0.693 | 0.83 | 850 | 0.6930 | -0.0002 | -0.0005 | 0.4462 | 0.0003 | -16.8842 | -15.2548 | -3.3537 | -3.3538 | |
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| 0.6926 | 0.88 | 900 | 0.6930 | -0.0000 | -0.0004 | 0.4571 | 0.0004 | -16.8832 | -15.2532 | -3.3537 | -3.3538 | |
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| 0.6937 | 0.93 | 950 | 0.6930 | -0.0000 | -0.0004 | 0.4571 | 0.0004 | -16.8832 | -15.2532 | -3.3537 | -3.3538 | |
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| 0.6926 | 0.98 | 1000 | 0.6930 | -0.0000 | -0.0004 | 0.4571 | 0.0004 | -16.8832 | -15.2532 | -3.3537 | -3.3538 | |
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### Framework versions |
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- Transformers 4.39.1 |
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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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