shawgpt-ft
This model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.2-GPTQ on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.9800
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: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use paged_adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
4.5922 | 0.9231 | 3 | 3.9586 |
4.041 | 1.8462 | 6 | 3.4341 |
3.4744 | 2.7692 | 9 | 2.9952 |
2.2714 | 4.0 | 13 | 2.5796 |
2.7159 | 4.9231 | 16 | 2.4308 |
2.501 | 5.8462 | 19 | 2.2380 |
2.3221 | 6.7692 | 22 | 2.1414 |
1.6694 | 8.0 | 26 | 2.0941 |
2.1571 | 8.9231 | 29 | 1.9993 |
1.4553 | 9.2308 | 30 | 1.9800 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.3
- Pytorch 2.0.1+cu117
- Datasets 2.19.1
- Tokenizers 0.20.3
- Downloads last month
- 3
Model tree for yongqianghf/shawgpt-ft
Base model
mistralai/Mistral-7B-Instruct-v0.2
Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ