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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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- generated_from_trainer |
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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-test-longest-iter-2 |
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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-test-longest-iter-2 |
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This model is a fine-tuned version of [DUAL-GPO/phi-2-gpo-test-longest-iter-1](https://huggingface.co/DUAL-GPO/phi-2-gpo-test-longest-iter-1) on the HuggingFaceH4/ultrafeedback_binarized dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0108 |
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- Rewards/chosen: -0.0005 |
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- Rewards/rejected: -0.0003 |
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- Rewards/accuracies: 0.4915 |
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- Rewards/margins: -0.0001 |
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- Logps/rejected: -278.6774 |
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- Logps/chosen: -306.4169 |
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- Logits/rejected: 0.0876 |
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- Logits/chosen: -0.0097 |
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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: 2 |
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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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| 0.0103 | 1.6 | 100 | 0.0108 | 0.0006 | 0.0007 | 0.5005 | -0.0000 | -278.5776 | -306.3062 | 0.0866 | -0.0109 | |
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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 2.2.1+cu121 |
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- Datasets 2.14.6 |
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- Tokenizers 0.15.2 |
