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--- |
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base_model: microsoft/Phi-3-mini-128k-instruct |
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library_name: peft |
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license: mit |
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tags: |
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- llama-factory |
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- lora |
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- generated_from_trainer |
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model-index: |
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- name: PairRM-V2-phi3-3-mini-unified-feedback |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/dongfu/huggingface/runs/336nlkkc) |
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# PairRM-V2-phi3-3-mini-unified-feedback |
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This model is a fine-tuned version of [microsoft/Phi-3-mini-128k-instruct](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct) on the all dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2755 |
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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: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 8 |
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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: 0.05 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.3099 | 0.3245 | 500 | 0.3066 | |
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| 0.3073 | 0.6490 | 1000 | 0.2901 | |
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| 0.263 | 0.9736 | 1500 | 0.2846 | |
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| 0.2822 | 1.2981 | 2000 | 0.2831 | |
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| 0.2693 | 1.6226 | 2500 | 0.2787 | |
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| 0.2741 | 1.9471 | 3000 | 0.2778 | |
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| 0.2869 | 2.2716 | 3500 | 0.2762 | |
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| 0.2339 | 2.5961 | 4000 | 0.2756 | |
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| 0.2879 | 2.9207 | 4500 | 0.2755 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.43.1 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
