PairRM-V2-phi3-3-mini-ultra-feedback-binarized-lora
This model is a fine-tuned version of microsoft/Phi-3-mini-128k-instruct on the ultra-feedback-binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.2605
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.2858 | 0.6406 | 500 | 0.2640 |
Framework versions
- PEFT 0.11.1
- Transformers 4.43.1
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for DongfuJiang/PairRM-V2-phi3-3-mini-ultra-feedback-binarized-lora
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microsoft/Phi-3-mini-128k-instruct
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