curated-gender-equality-weighted
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: 0.3517
- Accuracy: 0.9298
- F1: 0.8728
- Precision: 0.8629
- Recall: 0.8829
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: 1e-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: 20
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
---|---|---|---|---|---|---|---|
0.7794 | 1.0 | 342 | 0.5844 | 0.7357 | 0.6625 | 0.5084 | 0.9508 |
0.5228 | 2.0 | 684 | 0.4504 | 0.8588 | 0.7793 | 0.6795 | 0.9133 |
0.4184 | 3.0 | 1026 | 0.3897 | 0.8957 | 0.8242 | 0.7627 | 0.8963 |
0.3696 | 4.0 | 1368 | 0.3621 | 0.9083 | 0.8423 | 0.7937 | 0.8972 |
0.3354 | 5.0 | 1710 | 0.3667 | 0.9064 | 0.8369 | 0.7976 | 0.8803 |
0.3079 | 6.0 | 2052 | 0.3525 | 0.9122 | 0.8459 | 0.8118 | 0.8829 |
0.2927 | 7.0 | 2394 | 0.3373 | 0.9181 | 0.8552 | 0.8260 | 0.8865 |
0.2741 | 8.0 | 2736 | 0.3219 | 0.9252 | 0.8668 | 0.8423 | 0.8928 |
0.2627 | 9.0 | 3078 | 0.3576 | 0.9147 | 0.8481 | 0.8245 | 0.8731 |
0.2528 | 10.0 | 3420 | 0.3306 | 0.9266 | 0.8685 | 0.8496 | 0.8883 |
0.2398 | 11.0 | 3762 | 0.3336 | 0.9281 | 0.8703 | 0.8564 | 0.8847 |
0.2318 | 12.0 | 4104 | 0.3289 | 0.9308 | 0.8751 | 0.8615 | 0.8892 |
0.2234 | 13.0 | 4446 | 0.3438 | 0.9271 | 0.8683 | 0.8559 | 0.8811 |
0.2169 | 14.0 | 4788 | 0.3311 | 0.9327 | 0.8787 | 0.8643 | 0.8937 |
0.2126 | 15.0 | 5130 | 0.3444 | 0.9288 | 0.8716 | 0.8580 | 0.8856 |
0.2078 | 16.0 | 5472 | 0.3442 | 0.9298 | 0.8734 | 0.8597 | 0.8874 |
0.206 | 17.0 | 5814 | 0.3520 | 0.9281 | 0.8699 | 0.8589 | 0.8811 |
0.1986 | 18.0 | 6156 | 0.3473 | 0.9305 | 0.8743 | 0.8632 | 0.8856 |
0.1958 | 19.0 | 6498 | 0.3502 | 0.9300 | 0.8732 | 0.8636 | 0.8829 |
0.1958 | 20.0 | 6840 | 0.3517 | 0.9298 | 0.8728 | 0.8629 | 0.8829 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.0.1
- Datasets 2.20.0
- Tokenizers 0.19.1
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