metadata
base_model: microsoft/Phi-3-mini-128k-instruct
library_name: peft
license: mit
tags:
- llama-factory
- lora
- generated_from_trainer
model-index:
- name: PairRM-V2-phi3-3-mini-unified-feedback
results: []
PairRM-V2-phi3-3-mini-unified-feedback
This model is a fine-tuned version of microsoft/Phi-3-mini-128k-instruct on the all dataset. It achieves the following results on the evaluation set:
- Loss: 0.2755
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.3099 | 0.3245 | 500 | 0.3066 |
| 0.3073 | 0.6490 | 1000 | 0.2901 |
| 0.263 | 0.9736 | 1500 | 0.2846 |
| 0.2822 | 1.2981 | 2000 | 0.2831 |
| 0.2693 | 1.6226 | 2500 | 0.2787 |
| 0.2741 | 1.9471 | 3000 | 0.2778 |
| 0.2869 | 2.2716 | 3500 | 0.2762 |
| 0.2339 | 2.5961 | 4000 | 0.2756 |
| 0.2879 | 2.9207 | 4500 | 0.2755 |
Framework versions
- PEFT 0.11.1
- Transformers 4.43.1
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1