bert-finetuned-gender_classification
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1484
- F1: 0.9645
- Roc Auc: 0.9732
- Accuracy: 0.964
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: 10
Training results
Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
---|---|---|---|---|---|---|
0.1679 | 1.0 | 1125 | 0.1781 | 0.928 | 0.946 | 0.927 |
0.1238 | 2.0 | 2250 | 0.1252 | 0.9516 | 0.9640 | 0.95 |
0.0863 | 3.0 | 3375 | 0.1283 | 0.9515 | 0.9637 | 0.95 |
0.0476 | 4.0 | 4500 | 0.1419 | 0.9565 | 0.9672 | 0.956 |
0.0286 | 5.0 | 5625 | 0.1428 | 0.9555 | 0.9667 | 0.954 |
0.0091 | 6.0 | 6750 | 0.1515 | 0.9604 | 0.9700 | 0.959 |
0.0157 | 7.0 | 7875 | 0.1535 | 0.9580 | 0.9682 | 0.957 |
0.0048 | 8.0 | 9000 | 0.1484 | 0.9645 | 0.9732 | 0.964 |
0.0045 | 9.0 | 10125 | 0.1769 | 0.9605 | 0.9703 | 0.96 |
0.0037 | 10.0 | 11250 | 0.2007 | 0.9565 | 0.9672 | 0.956 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
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