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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_300steps_1e8rate_01beta_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_300steps_1e8rate_01beta_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: 0.6653 |
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- Rewards/chosen: 0.0172 |
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- Rewards/rejected: -0.0396 |
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- Rewards/accuracies: 0.9100 |
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- Rewards/margins: 0.0568 |
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- Logps/rejected: -80.3192 |
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- Logps/chosen: -47.9599 |
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- Logits/rejected: -2.5356 |
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- Logits/chosen: -2.5482 |
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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: 300 |
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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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| 0.6929 | 0.2667 | 50 | 0.6931 | -0.0010 | -0.0014 | 0.5700 | 0.0003 | -79.9371 | -48.1427 | -2.5355 | -2.5481 | |
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| 0.6881 | 0.5333 | 100 | 0.6832 | 0.0062 | -0.0142 | 0.6900 | 0.0204 | -80.0656 | -48.0704 | -2.5357 | -2.5482 | |
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| 0.67 | 0.8 | 150 | 0.6690 | 0.0151 | -0.0343 | 0.9000 | 0.0494 | -80.2661 | -47.9813 | -2.5359 | -2.5485 | |
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| 0.6726 | 1.0667 | 200 | 0.6633 | 0.0167 | -0.0444 | 0.9500 | 0.0611 | -80.3677 | -47.9656 | -2.5356 | -2.5482 | |
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| 0.6615 | 1.3333 | 250 | 0.6653 | 0.0172 | -0.0396 | 0.9100 | 0.0568 | -80.3192 | -47.9599 | -2.5356 | -2.5482 | |
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| 0.667 | 1.6 | 300 | 0.6653 | 0.0172 | -0.0396 | 0.9100 | 0.0568 | -80.3192 | -47.9599 | -2.5356 | -2.5482 | |
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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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