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: 1.6892
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 |
|---|---|---|---|
| 4.59 | 0.9231 | 3 | 3.9572 |
| 4.0294 | 1.8462 | 6 | 3.4287 |
| 3.4418 | 2.7692 | 9 | 2.9658 |
| 2.2281 | 4.0 | 13 | 2.5275 |
| 2.6155 | 4.9231 | 16 | 2.2658 |
| 2.2743 | 5.8462 | 19 | 2.0346 |
| 1.9913 | 6.7692 | 22 | 1.8587 |
| 1.3895 | 8.0 | 26 | 1.7372 |
| 1.7609 | 8.9231 | 29 | 1.6943 |
| 1.2289 | 9.2308 | 30 | 1.6892 |
Framework versions
- PEFT 0.13.0
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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Model tree for thom126f/shawgpt-ft
Base model
mistralai/Mistral-7B-Instruct-v0.2
Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ