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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: 4449.9023 |
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- Rewards/chosen: -0.8766 |
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- Rewards/rejected: -0.9587 |
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- Rewards/accuracies: 0.6161 |
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- Rewards/margins: 0.0822 |
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- Rewards/safe Rewards: -0.8653 |
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- Rewards/unsafe Rewards: -0.8608 |
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- Logps/rejected: -198.0037 |
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- Logps/chosen: -228.0047 |
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- Logits/rejected: 1.7482 |
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- Logits/chosen: 0.9054 |
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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: 4 |
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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: 64 |
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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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| 5410.1973 | 0.27 | 500 | 4657.3340 | -0.6508 | -0.7493 | 0.6367 | 0.0984 | -0.6382 | -0.6354 | -177.0600 | -205.4323 | 0.6948 | -0.0099 | |
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| 5634.6316 | 0.53 | 1000 | 4507.8945 | -0.8000 | -0.8748 | 0.6152 | 0.0748 | -0.7886 | -0.7846 | -189.6167 | -220.3491 | 1.1542 | 0.4120 | |
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| 5749.5141 | 0.8 | 1500 | 4458.4429 | -0.8858 | -0.9723 | 0.6194 | 0.0865 | -0.8741 | -0.8700 | -199.3641 | -228.9305 | 1.9547 | 1.0718 | |
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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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