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: 1.7352
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 |
---|---|---|---|
4.5888 | 0.9231 | 3 | 3.9471 |
4.0204 | 1.8462 | 6 | 3.4078 |
3.4323 | 2.7692 | 9 | 2.9436 |
2.2189 | 4.0 | 13 | 2.5111 |
2.616 | 4.9231 | 16 | 2.2696 |
2.2995 | 5.8462 | 19 | 2.0775 |
2.0688 | 6.7692 | 22 | 1.9201 |
1.4334 | 8.0 | 26 | 1.7803 |
1.8126 | 8.9231 | 29 | 1.7400 |
1.2626 | 9.2308 | 30 | 1.7352 |
Framework versions
- PEFT 0.13.0
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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Model tree for nastanda/shawgpt-ft
Base model
mistralai/Mistral-7B-Instruct-v0.2
Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ