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: 1.9343
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 |
---|---|---|---|
4.5928 | 0.92 | 3 | 3.9604 |
4.0485 | 1.85 | 6 | 3.4405 |
3.479 | 2.77 | 9 | 2.9924 |
2.2709 | 4.0 | 13 | 2.5757 |
2.7078 | 4.92 | 16 | 2.3559 |
2.419 | 5.85 | 19 | 2.1786 |
2.224 | 6.77 | 22 | 2.0678 |
1.5823 | 8.0 | 26 | 1.9969 |
2.0582 | 8.92 | 29 | 1.9493 |
1.4238 | 9.23 | 30 | 1.9343 |
Framework versions
- PEFT 0.9.0
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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Model tree for JoLiu/shawgpt-ft
Base model
mistralai/Mistral-7B-Instruct-v0.2
Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ