ewupersona_QA_lora_2000
This model is a fine-tuned version of shenzhi-wang/Llama3-8B-Chinese-Chat on the ewupersona_QA dataset. It achieves the following results on the evaluation set:
- Loss: 0.9173
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: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- total_eval_batch_size: 16
- 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 |
---|---|---|---|
0.7942 | 4.0 | 200 | 0.9173 |
Framework versions
- PEFT 0.12.0
- Transformers 4.43.3
- Pytorch 2.4.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Downloads last month
- 0
Model tree for hvgg1ngface/ewupersona_QA_lora_2000
Base model
meta-llama/Meta-Llama-3-8B-Instruct
Finetuned
shenzhi-wang/Llama3-8B-Chinese-Chat
Adapter
this model