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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-spo-shift |
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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-spo-shift |
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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: 0.6777 |
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- Rewards/chosen: -0.1371 |
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- Rewards/rejected: -0.0830 |
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- Rewards/accuracies: 0.4693 |
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- Rewards/margins: -0.0541 |
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- Rewards/safe Rewards: -0.1332 |
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- Rewards/unsafe Rewards: -0.1263 |
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- Logps/rejected: -92.4348 |
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- Logps/chosen: -131.0029 |
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- Logits/rejected: -1.8308 |
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- Logits/chosen: -2.0825 |
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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: 2 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 16 |
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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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| 131.6857 | 0.27 | 500 | 0.8894 | -0.1023 | -0.0129 | 0.4546 | -0.0893 | -0.1043 | -0.1017 | -92.3648 | -130.9681 | -1.8032 | -2.0565 | |
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| 34.7958 | 0.54 | 1000 | 0.7397 | -0.1263 | -0.1290 | 0.5028 | 0.0026 | -0.1237 | -0.1264 | -92.4809 | -130.9922 | -1.7990 | -2.0551 | |
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| 15.9924 | 0.81 | 1500 | 0.6823 | -0.1578 | -0.1077 | 0.4713 | -0.0501 | -0.1557 | -0.1535 | -92.4596 | -131.0237 | -1.8335 | -2.0849 | |
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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 0.15.2 |
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