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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/Na_M2_1000steps_1e7_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: Na_M2_100steps_1e7rate_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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# Na_M2_100steps_1e7rate_03beta_cSFTDPO |
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This model is a fine-tuned version of [tsavage68/Na_M2_1000steps_1e7_SFT](https://huggingface.co/tsavage68/Na_M2_1000steps_1e7_SFT) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0000 |
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- Rewards/chosen: 2.8383 |
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- Rewards/rejected: -9.2541 |
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- Rewards/accuracies: 1.0 |
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- Rewards/margins: 12.0924 |
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- Logps/rejected: -110.7703 |
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- Logps/chosen: -38.6713 |
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- Logits/rejected: -2.5103 |
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- Logits/chosen: -2.5250 |
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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-07 |
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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: 100 |
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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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| 0.0004 | 0.2667 | 50 | 0.0000 | 2.3360 | -8.0685 | 1.0 | 10.4045 | -106.8185 | -40.3458 | -2.5169 | -2.5309 | |
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| 0.0 | 0.5333 | 100 | 0.0000 | 2.8383 | -9.2541 | 1.0 | 12.0924 | -110.7703 | -38.6713 | -2.5103 | -2.5250 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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