README.md

---
library_name: transformers
license: apache-2.0
language:
- ja
datasets:
- HachiML/self-rewarding_AIFT_MSv0.3_lora
tags:
- self-rewarding
---

# Mistral-7B-v0.3-m3-lora

<!-- Provide a quick summary of what the model is/does. -->

 - [HachiML/Mistral-7B-v0.3-dpo-lora_sr_m3_lr1e-5_3ep](https://huggingface.co/HachiML/Mistral-7B-v0.3-dpo-lora_sr_m3_lr1e-5_3ep)のAdapterをマージしたモデル
 - This model is a fine-tuned version of [HachiML/Mistral-7B-v0.3-m2-lora](https://huggingface.co/HachiML/Mistral-7B-v0.3-m2-lora) on following datasets.
   - [HachiML/self-rewarding_AIFT_MSv0.3_lora](https://huggingface.co/datasets/HachiML/self-rewarding_AIFT_MSv0.3_lora)(split=AIFT_M2)


## Model Details

### Model Description

<!-- Provide a longer summary of what this model is. -->

This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

- **Developed by:** [HachiML](https://huggingface.co/HachiML)
- **Model type:** Mistral-7B
- **Language(s) (NLP):** Japanese
- **License:** Apache-2.0
- **Finetuned from model:** [HachiML/Mistral-7B-v0.3-m2-lora](https://huggingface.co/HachiML/Mistral-7B-v0.3-m2-lora)
- **Finetuned type:** DPO
- **Finetuned dataset:** [HachiML/self-rewarding_AIFT_MSv0.3_lora](https://huggingface.co/datasets/HachiML/self-rewarding_AIFT_MSv0.3_lora)(split=AIFT_M2)

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- 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

[<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/siseikatu8/huggingface/runs/wbj12r5j)  

### Framework versions

- PEFT 0.11.1
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1