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: 1.8412
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: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
4.4863 | 0.92 | 3 | 3.8282 |
3.8832 | 1.85 | 6 | 3.2503 |
3.2649 | 2.77 | 9 | 2.8113 |
2.1318 | 4.0 | 13 | 2.4031 |
2.4936 | 4.92 | 16 | 2.1910 |
2.245 | 5.85 | 19 | 2.0683 |
2.0828 | 6.77 | 22 | 1.9341 |
1.47 | 8.0 | 26 | 1.8721 |
1.9165 | 8.92 | 29 | 1.8499 |
1.3272 | 9.23 | 30 | 1.8412 |
Framework versions
- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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Model tree for ghegfield/shawgpt-ft
Base model
mistralai/Mistral-7B-Instruct-v0.2
Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ