shawgpt-ft-optuna
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: 1.3283
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: 0.0022807991454406587
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 4
- num_epochs: 13
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
7.5176 | 0.5714 | 1 | 4.2400 |
3.2331 | 1.7143 | 3 | 3.1222 |
2.3374 | 2.8571 | 5 | 2.1483 |
1.6067 | 4.0 | 7 | 1.4904 |
2.3372 | 4.5714 | 8 | 1.4033 |
0.9788 | 5.7143 | 10 | 1.3462 |
0.9133 | 6.8571 | 12 | 1.3295 |
0.8018 | 7.4286 | 13 | 1.3283 |
Framework versions
- PEFT 0.13.2
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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Model tree for Shaurya-Shsin/shawgpt-ft-optuna
Base model
mistralai/Mistral-7B-Instruct-v0.2
Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ