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shawgpt-ft4
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: 2.7517
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.1354 | 1.0 | 1 | 4.2318 |
| 2.1268 | 2.0 | 2 | 4.1433 |
| 2.0717 | 3.0 | 3 | 3.9443 |
| 1.978 | 4.0 | 4 | 3.7584 |
| 1.8766 | 5.0 | 5 | 3.5920 |
| 1.7922 | 6.0 | 6 | 3.4372 |
| 1.7215 | 7.0 | 7 | 3.2960 |
| 1.6398 | 8.0 | 8 | 3.1710 |
| 1.582 | 9.0 | 9 | 3.0635 |
| 1.5468 | 10.0 | 10 | 2.9731 |
| 1.4888 | 11.0 | 11 | 2.8988 |
| 1.4533 | 12.0 | 12 | 2.8398 |
| 1.4204 | 13.0 | 13 | 2.7961 |
| 1.3977 | 14.0 | 14 | 2.7667 |
| 1.3837 | 15.0 | 15 | 2.7517 |
Framework versions
- PEFT 0.13.2
- Transformers 4.44.2
- Pytorch 2.5.0+cu124
- Datasets 3.0.2
- Tokenizers 0.19.1
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Model tree for nour-sam/shawgpt-ft4
Base model
mistralai/Mistral-7B-Instruct-v0.2
Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ