| | --- |
| | license: gpl-3.0 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - precision |
| | - recall |
| | - f1 |
| | model-index: |
| | - name: test3 |
| | results: [] |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # test3 |
| |
|
| | This model is a fine-tuned version of [jcblaise/bert-tagalog-base-cased](https://huggingface.co/jcblaise/bert-tagalog-base-cased) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.3960 |
| | - Accuracy: 0.8683 |
| | - Precision: 0.8316 |
| | - Recall: 0.8653 |
| | - F1: 0.8481 |
| |
|
| | ## 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-05 |
| | - train_batch_size: 64 |
| | - eval_batch_size: 64 |
| | - 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 | Accuracy | Precision | Recall | F1 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | | No log | 1.0 | 151 | 0.3770 | 0.8431 | 0.8287 | 0.7951 | 0.8115 | |
| | | No log | 2.0 | 302 | 0.3561 | 0.8528 | 0.7959 | 0.8790 | 0.8354 | |
| | | No log | 3.0 | 453 | 0.3425 | 0.8647 | 0.8636 | 0.8094 | 0.8356 | |
| | | 0.3579 | 4.0 | 604 | 0.3541 | 0.8615 | 0.8090 | 0.8824 | 0.8441 | |
| | | 0.3579 | 5.0 | 755 | 0.3717 | 0.8611 | 0.8075 | 0.8836 | 0.8438 | |
| | | 0.3579 | 6.0 | 906 | 0.3657 | 0.8691 | 0.8352 | 0.8619 | 0.8483 | |
| | | 0.1703 | 7.0 | 1057 | 0.3826 | 0.8700 | 0.8370 | 0.8619 | 0.8493 | |
| | | 0.1703 | 8.0 | 1208 | 0.3960 | 0.8683 | 0.8316 | 0.8653 | 0.8481 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.26.1 |
| | - Pytorch 1.13.1+cu116 |
| | - Datasets 2.10.0 |
| | - Tokenizers 0.13.2 |
| |
|
