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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: 1.3086
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: 0.0003
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
4.562 | 0.9231 | 3 | 3.8136 |
3.7584 | 1.8462 | 6 | 3.0439 |
2.9884 | 2.7692 | 9 | 2.5154 |
1.8103 | 4.0 | 13 | 1.9763 |
1.9109 | 4.9231 | 16 | 1.6535 |
1.543 | 5.8462 | 19 | 1.4627 |
1.352 | 6.7692 | 22 | 1.3896 |
0.9888 | 8.0 | 26 | 1.3458 |
1.2644 | 8.9231 | 29 | 1.3269 |
1.2035 | 9.8462 | 32 | 1.3169 |
1.198 | 10.7692 | 35 | 1.3156 |
0.8476 | 12.0 | 39 | 1.3114 |
1.1265 | 12.9231 | 42 | 1.3086 |
1.0791 | 13.8462 | 45 | 1.3138 |
1.0711 | 14.7692 | 48 | 1.3207 |
0.7968 | 16.0 | 52 | 1.3141 |
1.0279 | 16.9231 | 55 | 1.3216 |
1.0094 | 17.8462 | 58 | 1.3262 |
0.7129 | 18.4615 | 60 | 1.3255 |
Framework versions
- PEFT 0.13.2
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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Model tree for LineLS/shawgpt-ft
Base model
mistralai/Mistral-7B-Instruct-v0.2
Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ