mean-pooled-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: 0.2068
- Accuracy: 0.9508
- F1: 0.9370
- Precision: 0.9065
- Recall: 0.9697
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
---|---|---|---|---|---|---|---|
0.4392 | 1.0 | 342 | 0.2876 | 0.9078 | 0.8878 | 0.8219 | 0.9651 |
0.2471 | 2.0 | 684 | 0.2366 | 0.9361 | 0.9198 | 0.8748 | 0.9697 |
0.2048 | 3.0 | 1026 | 0.2143 | 0.9539 | 0.9407 | 0.9156 | 0.9671 |
0.1847 | 4.0 | 1368 | 0.2080 | 0.9498 | 0.9357 | 0.9053 | 0.9684 |
0.1706 | 5.0 | 1710 | 0.2068 | 0.9508 | 0.9370 | 0.9065 | 0.9697 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1
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Model tree for alex-miller/mean-pooled-gender
Base model
google-bert/bert-base-multilingual-uncased
Finetuned
alex-miller/ODABert