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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: 1.3923
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: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 4.5447 | 0.9231 | 3 | 3.7620 |
| 3.7057 | 1.8462 | 6 | 3.0314 |
| 2.9605 | 2.7692 | 9 | 2.5033 |
| 1.7911 | 4.0 | 13 | 1.9813 |
| 1.9491 | 4.9231 | 16 | 1.7182 |
| 1.6483 | 5.8462 | 19 | 1.5669 |
| 1.459 | 6.7692 | 22 | 1.4547 |
| 1.0513 | 8.0 | 26 | 1.4034 |
| 1.3681 | 8.9231 | 29 | 1.3933 |
| 0.9861 | 9.2308 | 30 | 1.3923 |
Framework versions
- PEFT 0.13.2
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1
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Model tree for KrishGoyani/shawgpt-ft
Base model
mistralai/Mistral-7B-Instruct-v0.2
Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ