<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
men_women_classifier_bert
This model is a fine-tuned version of bert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1398
- Accuracy: {'accuracy': 0.9724468085106382}
- F1: {'f1': 0.972452950776052}
- Precision: {'precision': 0.972499865295955}
- Recall: {'recall': 0.9724468085106382}
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: 5e-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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.1764 | 1.0 | 4374 | 0.1782 | {'accuracy': 0.9608510638297872} | {'f1': 0.9608659804838514} | {'precision': 0.9610202496605896} | {'recall': 0.9608510638297872} |
| 0.1401 | 2.0 | 8748 | 0.1601 | {'accuracy': 0.9682978723404255} | {'f1': 0.9682853260342723} | {'precision': 0.9683573810256226} | {'recall': 0.9682978723404255} |
| 0.1209 | 3.0 | 13122 | 0.1395 | {'accuracy': 0.9730851063829787} | {'f1': 0.9730804185919066} | {'precision': 0.973094316365323} | {'recall': 0.9730851063829787} |
| 0.0858 | 4.0 | 17496 | 0.1398 | {'accuracy': 0.9724468085106382} | {'f1': 0.972452950776052} | {'precision': 0.972499865295955} | {'recall': 0.9724468085106382} |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
