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--- |
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license: mit |
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tags: |
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- generated_from_trainer |
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datasets: |
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- tapaco |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: punctuation-taboa-bert |
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results: |
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- task: |
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name: Token Classification |
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type: token-classification |
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dataset: |
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name: tapaco |
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type: tapaco |
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config: all_languages |
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split: train |
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args: all_languages |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.9849559686888454 |
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- name: Recall |
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type: recall |
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value: 0.9836325882496642 |
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- name: F1 |
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type: f1 |
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value: 0.9842938336490864 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9945622875893589 |
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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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# punctuation-taboa-bert |
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This model is a fine-tuned version of [neuralmind/bert-large-portuguese-cased](https://huggingface.co/neuralmind/bert-large-portuguese-cased) on the tapaco dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0181 |
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- Precision: 0.9850 |
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- Recall: 0.9836 |
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- F1: 0.9843 |
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- Accuracy: 0.9946 |
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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: 2e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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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: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 0.0272 | 1.0 | 17438 | 0.0181 | 0.9850 | 0.9836 | 0.9843 | 0.9946 | |
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| 0.0234 | 2.0 | 34876 | 0.0196 | 0.9870 | 0.9853 | 0.9862 | 0.9948 | |
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| 0.0092 | 3.0 | 52314 | 0.0233 | 0.9874 | 0.9853 | 0.9864 | 0.9950 | |
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### Framework versions |
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- Transformers 4.23.1 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.5.2 |
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- Tokenizers 0.13.1 |
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