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: 1.1894
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 |
|---|---|---|---|
| 3.2906 | 0.96 | 6 | 2.6532 |
| 2.3956 | 1.92 | 12 | 2.1305 |
| 1.9455 | 2.88 | 18 | 1.8162 |
| 1.3545 | 4.0 | 25 | 1.4919 |
| 1.3298 | 4.96 | 31 | 1.3596 |
| 1.204 | 5.92 | 37 | 1.2877 |
| 1.1487 | 6.88 | 43 | 1.2487 |
| 0.9525 | 8.0 | 50 | 1.2124 |
| 1.0795 | 8.96 | 56 | 1.1934 |
| 0.9947 | 9.6 | 60 | 1.1894 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for dapraws/shawgpt-ft
Base model
mistralai/Mistral-7B-Instruct-v0.2
Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ