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README.md
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---
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license: gpl-3.0
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- precision
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- recall
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- f1
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model-index:
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- name: test2
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# test2
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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.
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It achieves the following results on the evaluation set:
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- Loss: 0.4185
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- Accuracy: 0.8669
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- Precision: 0.8249
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- Recall: 0.8612
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- F1: 0.8426
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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- train_batch_size: 64
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- eval_batch_size: 64
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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| No log | 1.0 | 172 | 0.3674 | 0.8444 | 0.8014 | 0.8295 | 0.8152 |
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| No log | 2.0 | 344 | 0.3508 | 0.8542 | 0.8235 | 0.8243 | 0.8239 |
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| 0.2992 | 3.0 | 516 | 0.3643 | 0.8564 | 0.8596 | 0.7803 | 0.8181 |
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| 0.2992 | 4.0 | 688 | 0.3639 | 0.8622 | 0.8155 | 0.8620 | 0.8381 |
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| 0.2992 | 5.0 | 860 | 0.3803 | 0.864 | 0.8316 | 0.8418 | 0.8367 |
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| 0.1733 | 6.0 | 1032 | 0.3969 | 0.8702 | 0.8352 | 0.8550 | 0.8450 |
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| 0.1733 | 7.0 | 1204 | 0.4185 | 0.8669 | 0.8249 | 0.8612 | 0.8426 |
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### Framework versions
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- Transformers 4.26.1
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- Pytorch 1.13.1+cu116
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- Tokenizers 0.13.2
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