distilbert-base-uncased-text-classification-v5
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: 0.2879
- F1: 0.8471
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: 10
Training results
Training Loss | Epoch | Step | Validation Loss | F1 |
---|---|---|---|---|
1.3863 | 1.0 | 569 | 0.7220 | 0.4679 |
0.6212 | 2.0 | 1138 | 0.4596 | 0.6839 |
0.3746 | 3.0 | 1707 | 0.3441 | 0.7901 |
0.2685 | 4.0 | 2276 | 0.3036 | 0.8204 |
0.172 | 5.0 | 2845 | 0.2884 | 0.8289 |
0.1328 | 6.0 | 3414 | 0.2879 | 0.8471 |
0.1068 | 7.0 | 3983 | 0.2957 | 0.8400 |
0.0757 | 8.0 | 4552 | 0.2917 | 0.8464 |
0.0693 | 9.0 | 5121 | 0.2931 | 0.8404 |
0.0651 | 10.0 | 5690 | 0.2921 | 0.8428 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.13.3
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