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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: tsavage68/IE_M2_1000steps_1e7rate_SFT |
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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: IE_M2_350steps_1e8rate_03beta_cSFTDPO |
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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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# IE_M2_350steps_1e8rate_03beta_cSFTDPO |
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This model is a fine-tuned version of [tsavage68/IE_M2_1000steps_1e7rate_SFT](https://huggingface.co./tsavage68/IE_M2_1000steps_1e7rate_SFT) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6746 |
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- Rewards/chosen: -0.0013 |
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- Rewards/rejected: -0.0404 |
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- Rewards/accuracies: 0.3600 |
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- Rewards/margins: 0.0391 |
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- Logps/rejected: -41.1564 |
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- Logps/chosen: -42.2098 |
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- Logits/rejected: -2.9159 |
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- Logits/chosen: -2.8545 |
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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: 350 |
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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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| 0.6998 | 0.4 | 50 | 0.6949 | 0.0058 | 0.0085 | 0.2050 | -0.0028 | -40.9934 | -42.1863 | -2.9160 | -2.8547 | |
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| 0.6925 | 0.8 | 100 | 0.6906 | 0.0017 | -0.0041 | 0.2600 | 0.0059 | -41.0355 | -42.1997 | -2.9159 | -2.8546 | |
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| 0.679 | 1.2 | 150 | 0.6779 | 0.0047 | -0.0273 | 0.3650 | 0.0320 | -41.1127 | -42.1899 | -2.9158 | -2.8546 | |
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| 0.6715 | 1.6 | 200 | 0.6747 | 0.0020 | -0.0367 | 0.3900 | 0.0387 | -41.1442 | -42.1988 | -2.9156 | -2.8544 | |
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| 0.6764 | 2.0 | 250 | 0.6736 | -0.0012 | -0.0419 | 0.3850 | 0.0407 | -41.1614 | -42.2094 | -2.9156 | -2.8543 | |
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| 0.6842 | 2.4 | 300 | 0.6763 | -0.0024 | -0.0380 | 0.3500 | 0.0355 | -41.1483 | -42.2137 | -2.9159 | -2.8545 | |
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| 0.6712 | 2.8 | 350 | 0.6746 | -0.0013 | -0.0404 | 0.3600 | 0.0391 | -41.1564 | -42.2098 | -2.9159 | -2.8545 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.0.0+cu117 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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