unpooled-gender
This model is a fine-tuned version of alex-miller/ODABert on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3196
- Accuracy: 0.9269
- F1: 0.9071
- Precision: 0.8715
- Recall: 0.9458
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-06
- train_batch_size: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
---|---|---|---|---|---|---|---|
1.0053 | 1.0 | 342 | 0.5759 | 0.8613 | 0.8326 | 0.7649 | 0.9135 |
0.4624 | 2.0 | 684 | 0.3887 | 0.9083 | 0.8858 | 0.8365 | 0.9413 |
0.3385 | 3.0 | 1026 | 0.3461 | 0.9274 | 0.9070 | 0.8775 | 0.9387 |
0.2909 | 4.0 | 1368 | 0.3244 | 0.9259 | 0.9057 | 0.8716 | 0.9425 |
0.2699 | 5.0 | 1710 | 0.3196 | 0.9269 | 0.9071 | 0.8715 | 0.9458 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for alex-miller/unpooled-gender
Base model
google-bert/bert-base-multilingual-uncased
Finetuned
alex-miller/ODABert