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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: 1.5962
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: 0.001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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 |
|---|---|---|---|
| 4.3235 | 1.0 | 1 | 4.2320 |
| 4.1409 | 2.0 | 2 | 3.8759 |
| 3.882 | 3.0 | 3 | 3.1875 |
| 3.1693 | 4.0 | 4 | 2.6918 |
| 2.7522 | 5.0 | 5 | 2.3807 |
| 2.3379 | 6.0 | 6 | 2.1297 |
| 2.0368 | 7.0 | 7 | 1.9097 |
| 1.824 | 8.0 | 8 | 1.7536 |
| 1.6601 | 9.0 | 9 | 1.6447 |
| 1.4733 | 10.0 | 10 | 1.5962 |
Framework versions
- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
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Model tree for tobiaskjensen/shawgpt-ft
Base model
mistralai/Mistral-7B-Instruct-v0.2
Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ