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---
base_model: shenzhi-wang/Llama3.1-70B-Chinese-Chat
library_name: peft
license: other
tags:
- llama-factory
- lora
- generated_from_trainer
model-index:
- name: Llama3.1-70B-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. -->
# Llama3.1-70B-Chinese-Chat
This model is a fine-tuned version of [shenzhi-wang/Llama3.1-70B-Chinese-Chat](https://huggingface.co/shenzhi-wang/Llama3.1-70B-Chinese-Chat) on the alpaca_mac dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5071
## 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: 2
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 6.0
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.4367 | 0.9982 | 70 | 1.3731 |
| 1.2601 | 1.9964 | 140 | 1.3131 |
| 0.8929 | 2.9947 | 210 | 1.4369 |
| 0.383 | 3.9929 | 280 | 1.7250 |
| 0.1431 | 4.9911 | 350 | 2.0897 |
| 0.0691 | 5.9893 | 420 | 2.5071 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.43.3
- Pytorch 2.4.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1