shawgpt-ft6
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: 4.1405
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: 2e-05
- 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 | 4.2295 |
2.1189 | 3.0 | 3 | 4.2188 |
2.1264 | 4.0 | 4 | 4.2077 |
2.1174 | 5.0 | 5 | 4.1971 |
2.1101 | 6.0 | 6 | 4.1873 |
2.1162 | 7.0 | 7 | 4.1781 |
2.0936 | 8.0 | 8 | 4.1703 |
2.0862 | 9.0 | 9 | 4.1631 |
2.113 | 10.0 | 10 | 4.1567 |
2.0867 | 11.0 | 11 | 4.1517 |
2.0956 | 12.0 | 12 | 4.1470 |
2.0801 | 13.0 | 13 | 4.1438 |
2.092 | 14.0 | 14 | 4.1417 |
2.0841 | 15.0 | 15 | 4.1405 |
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-ft6
Base model
mistralai/Mistral-7B-Instruct-v0.2
Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ