TinyMistral-specific-4bit
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: 1.1940
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: Use paged_adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.7744 | 0.8696 | 5 | 1.5917 |
1.3359 | 1.9130 | 11 | 1.4566 |
1.254 | 2.9565 | 17 | 1.3934 |
1.1805 | 4.0 | 23 | 1.3203 |
1.3421 | 4.8696 | 28 | 1.2766 |
1.0701 | 5.9130 | 34 | 1.2354 |
1.0341 | 6.9565 | 40 | 1.2107 |
1.0113 | 8.0 | 46 | 1.1974 |
1.0482 | 8.6957 | 50 | 1.1940 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3
- Downloads last month
- 10
Model tree for Dhanunjaiah/TinyMistral-specific-4bit
Base model
mistralai/Mistral-7B-Instruct-v0.2
Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ