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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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- 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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model-index: |
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- name: phi2-lora-distilabel-intel-orca-dpo-pairs |
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results: [] |
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--- |
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*Note from me: This is a fine tuned Phi-2 on Argilla-provided Intel Orca DPO pairs. It's run with the default settings, just with the batch sized at 2 instead of 1. The below was automatically generated by the trainer. It cost about $2.50 to train on RunPod.* |
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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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# phi2-lora-distilabel-intel-orca-dpo-pairs |
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This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4467 |
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- Rewards/chosen: -0.0981 |
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- Rewards/rejected: -1.3106 |
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- Rewards/accuracies: 0.8410 |
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- Rewards/margins: 1.2125 |
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- Logps/rejected: -228.4777 |
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- Logps/chosen: -209.0628 |
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- Logits/rejected: 0.4528 |
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- Logits/chosen: 0.2946 |
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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: 1e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 16 |
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- total_train_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: linear |
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- lr_scheduler_warmup_steps: 250 |
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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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| 0.5578 | 0.78 | 250 | 0.4467 | -0.0981 | -1.3106 | 0.8410 | 1.2125 | -228.4777 | -209.0628 | 0.4528 | 0.2946 | |
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### Framework versions |
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- PEFT 0.9.0 |
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- Transformers 4.38.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
