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--- |
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license: mit |
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library_name: peft |
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tags: |
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- alignment-handbook |
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- generated_from_trainer |
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- trl |
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- dpo |
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base_model: microsoft/phi-2 |
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datasets: |
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- HuggingFaceH4/ultrafeedback_binarized |
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model-index: |
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- name: phi-2-gpo-renew2-b0.001-extra-i1 |
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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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# phi-2-gpo-renew2-b0.001-extra-i1 |
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This model is a fine-tuned version of [DUAL-GPO/phi-2-gpo-renew2-b0.001-i0](https://huggingface.co/DUAL-GPO/phi-2-gpo-renew2-b0.001-i0) on the HuggingFaceH4/ultrafeedback_binarized dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0421 |
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- Rewards/chosen: -0.0100 |
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- Rewards/rejected: -0.0414 |
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- Rewards/accuracies: 0.6015 |
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- Rewards/margins: 0.0314 |
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- Logps/rejected: -408.6569 |
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- Logps/chosen: -406.3272 |
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- Logits/rejected: -1.0065 |
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- Logits/chosen: -1.0521 |
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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-06 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 4 |
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- total_train_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 | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |
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|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| |
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| 0.0982 | 0.11 | 100 | 0.0526 | -0.0081 | -0.0101 | 0.5190 | 0.0020 | -377.3773 | -404.4459 | -0.7816 | -0.8697 | |
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| 0.0846 | 0.21 | 200 | 0.0485 | -0.0265 | -0.0402 | 0.5530 | 0.0137 | -407.4654 | -422.8199 | -0.9792 | -1.0427 | |
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| 0.0859 | 0.32 | 300 | 0.0464 | -0.0257 | -0.0460 | 0.5725 | 0.0203 | -413.2813 | -422.0490 | -1.0612 | -1.1154 | |
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| 0.0957 | 0.43 | 400 | 0.0443 | -0.0207 | -0.0481 | 0.5780 | 0.0274 | -415.3487 | -417.0023 | -1.0450 | -1.0984 | |
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| 0.068 | 0.53 | 500 | 0.0432 | -0.0067 | -0.0318 | 0.5955 | 0.0252 | -399.0811 | -402.9732 | -0.9791 | -1.0329 | |
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| 0.0847 | 0.64 | 600 | 0.0427 | -0.0050 | -0.0312 | 0.5945 | 0.0263 | -398.4744 | -401.2879 | -0.9837 | -1.0364 | |
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| 0.0519 | 0.75 | 700 | 0.0423 | -0.0082 | -0.0377 | 0.5905 | 0.0295 | -404.9791 | -404.5331 | -0.9872 | -1.0360 | |
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| 0.0742 | 0.85 | 800 | 0.0422 | -0.0105 | -0.0420 | 0.6000 | 0.0315 | -409.2462 | -406.8035 | -1.0109 | -1.0556 | |
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| 0.0768 | 0.96 | 900 | 0.0421 | -0.0100 | -0.0415 | 0.5930 | 0.0315 | -408.7397 | -406.3475 | -1.0050 | -1.0502 | |
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### Framework versions |
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- PEFT 0.7.1 |
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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 |