MLMA_GPT_Lab8
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1546
- Precision: 0.4386
- Recall: 0.5311
- F1: 0.4805
- Accuracy: 0.9571
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 |
---|---|---|---|---|---|---|---|
0.2978 | 1.0 | 679 | 0.1732 | 0.2941 | 0.4536 | 0.3568 | 0.9424 |
0.1679 | 2.0 | 1358 | 0.1527 | 0.4004 | 0.5184 | 0.4518 | 0.9535 |
0.0963 | 3.0 | 2037 | 0.1546 | 0.4386 | 0.5311 | 0.4805 | 0.9571 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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