MLMA_Lab_8_GPT
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1501
- Precision: 0.4539
- Recall: 0.5382
- F1: 0.4924
- Accuracy: 0.9570
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.2907 | 1.0 | 679 | 0.1812 | 0.3208 | 0.3041 | 0.3122 | 0.9463 |
0.1689 | 2.0 | 1358 | 0.1456 | 0.3980 | 0.5165 | 0.4496 | 0.9536 |
0.0952 | 3.0 | 2037 | 0.1501 | 0.4539 | 0.5382 | 0.4924 | 0.9570 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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