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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: 1.3193
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: 0.0003
- 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: 20
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
4.549 | 0.9231 | 3 | 3.7742 |
3.7071 | 1.8462 | 6 | 3.0015 |
2.9311 | 2.7692 | 9 | 2.4539 |
1.7517 | 4.0 | 13 | 1.9081 |
1.8423 | 4.9231 | 16 | 1.5904 |
1.4838 | 5.8462 | 19 | 1.4268 |
1.3316 | 6.7692 | 22 | 1.3723 |
0.9811 | 8.0 | 26 | 1.3355 |
1.2579 | 8.9231 | 29 | 1.3238 |
1.2023 | 9.8462 | 32 | 1.3183 |
1.195 | 10.7692 | 35 | 1.3164 |
0.8422 | 12.0 | 39 | 1.3119 |
1.1189 | 12.9231 | 42 | 1.3117 |
1.0709 | 13.8462 | 45 | 1.3142 |
1.0589 | 14.7692 | 48 | 1.3155 |
0.7875 | 16.0 | 52 | 1.3143 |
1.0142 | 16.9231 | 55 | 1.3172 |
0.9965 | 17.8462 | 58 | 1.3190 |
0.7023 | 18.4615 | 60 | 1.3193 |
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 MonsMayli/shawgpt-ft
Base model
mistralai/Mistral-7B-Instruct-v0.2
Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ