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distilbert-base-uncased_log_classfication_v1
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3145
- Accuracy: 0.8957
- F1: 0.8788
- Precision: 0.6201
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: 32
- eval_batch_size: 32
- 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 | Accuracy | F1 | Precision |
|---|---|---|---|---|---|---|
| 0.6659 | 1.0 | 54 | 0.7349 | 0.8160 | 0.7867 | 0.5111 |
| 0.2695 | 2.0 | 108 | 0.3906 | 0.8773 | 0.8585 | 0.5924 |
| 0.1925 | 3.0 | 162 | 0.3145 | 0.8957 | 0.8788 | 0.6201 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
