semantic-bert-imbalanced-dataset
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: 3.3940
- Accuracy: 0.5926
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 367 | 0.8237 | 0.6017 |
0.7608 | 2.0 | 734 | 0.8750 | 0.5834 |
0.5139 | 3.0 | 1101 | 0.9829 | 0.5946 |
0.5139 | 4.0 | 1468 | 1.2406 | 0.5870 |
0.3119 | 5.0 | 1835 | 1.5168 | 0.5865 |
0.1501 | 6.0 | 2202 | 2.0461 | 0.5814 |
0.0981 | 7.0 | 2569 | 2.2575 | 0.5860 |
0.0981 | 8.0 | 2936 | 2.6289 | 0.5804 |
0.0647 | 9.0 | 3303 | 2.8079 | 0.5844 |
0.0436 | 10.0 | 3670 | 2.9811 | 0.5824 |
0.0271 | 11.0 | 4037 | 3.0669 | 0.5875 |
0.0271 | 12.0 | 4404 | 3.1201 | 0.5834 |
0.0153 | 13.0 | 4771 | 3.1980 | 0.5910 |
0.0189 | 14.0 | 5138 | 3.2317 | 0.5931 |
0.0158 | 15.0 | 5505 | 3.2659 | 0.5885 |
0.0158 | 16.0 | 5872 | 3.3860 | 0.5875 |
0.0122 | 17.0 | 6239 | 3.3302 | 0.5956 |
0.0107 | 18.0 | 6606 | 3.3341 | 0.5946 |
0.0107 | 19.0 | 6973 | 3.4042 | 0.5931 |
0.0078 | 20.0 | 7340 | 3.3940 | 0.5926 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.3.0.dev20231224
- Datasets 2.16.0
- Tokenizers 0.15.0
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