---
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: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

[<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)
# PairRM-V2-phi3-3-mini-unified-feedback

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.
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