shawgpt-ft-rank10
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: 1.9168
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: 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 |
---|---|---|---|
4.6289 | 0.9231 | 3 | 4.1390 |
4.3847 | 1.8462 | 6 | 3.8683 |
4.0422 | 2.7692 | 9 | 3.5768 |
2.7681 | 4.0 | 13 | 3.2026 |
3.3944 | 4.9231 | 16 | 2.9603 |
3.1075 | 5.8462 | 19 | 2.7572 |
2.8829 | 6.7692 | 22 | 2.5892 |
2.0129 | 8.0 | 26 | 2.3923 |
2.4989 | 8.9231 | 29 | 2.2593 |
2.3288 | 9.8462 | 32 | 2.1539 |
2.2272 | 10.7692 | 35 | 2.0619 |
1.5679 | 12.0 | 39 | 1.9692 |
2.0402 | 12.9231 | 42 | 1.9322 |
1.6878 | 13.8462 | 45 | 1.9168 |
Framework versions
- PEFT 0.13.2
- Transformers 4.44.2
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.19.1
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Model tree for FrederikKlinkby/shawgpt-ft-rank10
Base model
mistralai/Mistral-7B-Instruct-v0.2
Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ