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--- |
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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: dpo-selective-buffer-safeipo |
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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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# dpo-selective-buffer-safeipo |
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This model was trained from scratch on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3423 |
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- Rewards/chosen: -1.0061 |
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- Rewards/rejected: -1.3040 |
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- Rewards/accuracies: 0.7314 |
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- Rewards/margins: 0.2980 |
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- Rewards/safe Rewards: -0.9953 |
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- Rewards/unsafe Rewards: -1.0113 |
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- Logps/rejected: -222.8744 |
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- Logps/chosen: -231.0451 |
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- Logits/rejected: -0.6287 |
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- Logits/chosen: -1.0992 |
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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: 5e-07 |
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- train_batch_size: 2 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 32 |
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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_ratio: 0.1 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Rewards/safe Rewards | Rewards/unsafe Rewards | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |
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|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------------:|:----------------------:|:--------------:|:------------:|:---------------:|:-------------:| |
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| 1.0274 | 0.27 | 500 | 0.3731 | -1.0192 | -1.3005 | 0.7075 | 0.2813 | -1.0089 | -1.0281 | -222.5216 | -232.3561 | -0.9855 | -1.4616 | |
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| 0.9569 | 0.54 | 1000 | 0.3497 | -0.9136 | -1.2026 | 0.7210 | 0.2890 | -0.9006 | -0.9166 | -212.7308 | -221.7959 | -0.5821 | -1.0712 | |
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| 0.8619 | 0.81 | 1500 | 0.3429 | -0.9136 | -1.1772 | 0.7269 | 0.2635 | -0.9047 | -0.9192 | -210.1883 | -221.8018 | -0.7005 | -1.1466 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.14.6 |
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- Tokenizers 0.15.0 |
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