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: 1.8340
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 |
---|---|---|---|
0.4276 | 1.0 | 1 | 1.9583 |
0.4276 | 2.0 | 2 | 1.9512 |
0.4107 | 3.0 | 3 | 1.9324 |
0.3762 | 4.0 | 4 | 1.9108 |
0.3493 | 5.0 | 5 | 1.8891 |
0.3269 | 6.0 | 6 | 1.8698 |
0.3086 | 7.0 | 7 | 1.8545 |
0.2947 | 8.0 | 8 | 1.8435 |
0.2844 | 9.0 | 9 | 1.8370 |
0.2775 | 10.0 | 10 | 1.8340 |
Framework versions
- PEFT 0.11.0
- Transformers 4.40.2
- Pytorch 2.1.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for Keano95/shawgpt-ft
Base model
mistralai/Mistral-7B-Instruct-v0.2
Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ