---
base_model: shenzhi-wang/Llama3-8B-Chinese-Chat
library_name: peft
license: llama3
tags:
- llama-factory
- lora
- generated_from_trainer
model-index:
- name: wenjie_6k
  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. -->

# wenjie_6k

This model is a fine-tuned version of [shenzhi-wang/Llama3-8B-Chinese-Chat](https://huggingface.co/shenzhi-wang/Llama3-8B-Chinese-Chat) on the data_large2, the target_QA_short and the append_QA datasets.
It achieves the following results on the evaluation set:
- Loss: 0.9191

## 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: 8e-06
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 4

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.9918        | 2.1448 | 200  | 0.9989          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.43.3
- Pytorch 2.4.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1