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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: 1.9509
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 12
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
4.6204 | 0.9231 | 3 | 4.0975 |
4.2876 | 1.8462 | 6 | 3.7425 |
3.8607 | 2.7692 | 9 | 3.3912 |
2.5952 | 4.0 | 13 | 2.9728 |
3.1357 | 4.9231 | 16 | 2.7291 |
2.8442 | 5.8462 | 19 | 2.5357 |
2.6161 | 6.7692 | 22 | 2.3637 |
1.8139 | 8.0 | 26 | 2.1825 |
2.2632 | 8.9231 | 29 | 2.0778 |
2.1237 | 9.8462 | 32 | 1.9958 |
2.069 | 10.7692 | 35 | 1.9554 |
0.421 | 11.0769 | 36 | 1.9509 |
Framework versions
- PEFT 0.13.2
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1
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Model tree for TeisNN/shawgpt-ft
Base model
mistralai/Mistral-7B-Instruct-v0.2
Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ