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---
base_model: shenzhi-wang/Llama3.1-8B-Chinese-Chat
library_name: peft
license: other
tags:
- llama-factory
- lora
- generated_from_trainer
model-index:
- name: Llama3.1-8B-Chinese-Chat
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. -->
# Llama3.1-8B-Chinese-Chat
This model is a fine-tuned version of [shenzhi-wang/Llama3.1-8B-Chinese-Chat](https://huggingface.co/shenzhi-wang/Llama3.1-8B-Chinese-Chat) on the alpaca_mgtv_p2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2191
## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2.0
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.3253 | 0.1990 | 35 | 0.2875 |
| 0.2868 | 0.3980 | 70 | 0.2600 |
| 0.2583 | 0.5970 | 105 | 0.2508 |
| 0.2559 | 0.7960 | 140 | 0.2279 |
| 0.2516 | 0.9950 | 175 | 0.2221 |
| 0.2086 | 1.1940 | 210 | 0.2271 |
| 0.238 | 1.3930 | 245 | 0.2183 |
| 0.2176 | 1.5920 | 280 | 0.2206 |
| 0.2022 | 1.7910 | 315 | 0.2209 |
| 0.209 | 1.9900 | 350 | 0.2191 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.43.3
- Pytorch 2.4.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1 |