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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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datasets: |
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- HuggingFaceH4/ultrafeedback_binarized |
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base_model: microsoft/phi-2 |
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model-index: |
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- name: phi-2-gpo-ultrafeedback-lora |
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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-ultrafeedback-lora |
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This model is a fine-tuned version of [lole25/phi-2-sft-ultrachat-lora](https://huggingface.co/lole25/phi-2-sft-ultrachat-lora) on the HuggingFaceH4/ultrafeedback_binarized dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0004 |
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- Rewards/chosen: -0.0084 |
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- Rewards/rejected: -0.0177 |
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- Rewards/accuracies: 0.6700 |
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- Rewards/margins: 0.0093 |
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- Logps/rejected: -233.2047 |
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- Logps/chosen: -261.0818 |
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- Logits/rejected: 0.8824 |
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- Logits/chosen: 0.7796 |
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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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- 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: 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 | Logits/chosen | Logits/rejected | Logps/chosen | Logps/rejected | Validation Loss | Rewards/accuracies | Rewards/chosen | Rewards/margins | Rewards/rejected | |
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|:-------------:|:-----:|:----:|:-------------:|:---------------:|:------------:|:--------------:|:---------------:|:------------------:|:--------------:|:---------------:|:----------------:| |
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| 0.0026 | 0.21 | 100 | 0.8151 | 0.9175 | -260.2373 | -231.4896 | 0.0025 | 0.5080 | 0.0001 | 0.0006 | -0.0005 | |
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| 0.0023 | 0.42 | 200 | 0.8092 | 0.9120 | -260.3932 | -232.1152 | 0.0023 | 0.6560 | -0.0015 | 0.0053 | -0.0068 | |
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| 0.0022 | 0.63 | 300 | 0.7992 | 0.9022 | -260.9179 | -232.8447 | 0.0022 | 0.6700 | -0.0067 | 0.0073 | -0.0141 | |
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| 0.0021 | 0.84 | 400 | 0.7884 | 0.8914 | -261.1620 | -233.2157 | 0.0022 | 0.6640 | -0.0092 | 0.0086 | -0.0178 | |
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| 0.0022 | 1.05 | 500 | 0.7821 | 0.8853 | -261.1852 | -233.3614 | 0.0021 | 0.7100 | -0.0094 | 0.0098 | -0.0193 | |
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| 0.002 | 1.26 | 600 | 0.7815 | 0.8840 | -261.1207 | -233.2843 | 0.0021 | 0.6940 | -0.0088 | 0.0097 | -0.0185 | |
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| 0.0021 | 1.47 | 700 | 0.7790 | 0.8816 | -261.0788 | -233.2560 | 0.0021 | 0.7000 | -0.0083 | 0.0099 | -0.0182 | |
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| 0.0021 | 1.67 | 800 | 0.7781 | 0.8811 | -261.0643 | -233.2740 | 0.0021 | 0.6940 | -0.0082 | 0.0102 | -0.0184 | |
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| 0.0021 | 1.88 | 900 | 0.7806 | 0.8833 | -261.0922 | -233.2118 | 0.0021 | 0.6900 | -0.0085 | 0.0093 | -0.0178 | |
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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+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.15.2 |
