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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: 1.3181
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: 15
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
4.5648 | 0.9231 | 3 | 3.8322 |
3.7889 | 1.8462 | 6 | 3.0934 |
3.0308 | 2.7692 | 9 | 2.5481 |
1.8459 | 4.0 | 13 | 2.0266 |
1.9947 | 4.9231 | 16 | 1.7098 |
1.6157 | 5.8462 | 19 | 1.5266 |
1.4058 | 6.7692 | 22 | 1.4120 |
1.0081 | 8.0 | 26 | 1.3659 |
1.292 | 8.9231 | 29 | 1.3461 |
1.2306 | 9.8462 | 32 | 1.3329 |
1.2258 | 10.7692 | 35 | 1.3257 |
0.8719 | 12.0 | 39 | 1.3198 |
1.1711 | 12.9231 | 42 | 1.3186 |
0.9684 | 13.8462 | 45 | 1.3181 |
Framework versions
- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1
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Model tree for VanillaThunder/shawgpt-ft
Base model
mistralai/Mistral-7B-Instruct-v0.2
Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ