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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: google-bert/bert-base-multilingual-cased |
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tags: |
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- generated_from_trainer |
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datasets: |
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- told-br |
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metrics: |
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- precision |
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- recall |
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- accuracy |
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- f1 |
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model-index: |
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- name: bert-base-multilingual-cased-finetuned-hate-speech-ptbr |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: told-br |
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type: told-br |
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config: binary |
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split: validation |
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args: binary |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.702020202020202 |
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- name: Recall |
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type: recall |
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value: 0.7654185022026432 |
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- name: Accuracy |
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type: accuracy |
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value: 0.758095238095238 |
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- name: F1 |
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type: f1 |
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value: 0.7590123199739615 |
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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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# bert-base-multilingual-cased-finetuned-hate-speech-ptbr |
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This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the told-br dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6224 |
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- Precision: 0.7020 |
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- Recall: 0.7654 |
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- Accuracy: 0.7581 |
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- F1: 0.7590 |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:------:| |
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| 0.5127 | 1.0 | 1050 | 0.4978 | 0.6500 | 0.8756 | 0.7424 | 0.7418 | |
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| 0.4415 | 2.0 | 2100 | 0.5206 | 0.7143 | 0.7104 | 0.7519 | 0.7518 | |
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| 0.3623 | 3.0 | 3150 | 0.6204 | 0.6747 | 0.8293 | 0.7533 | 0.7542 | |
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| 0.283 | 4.0 | 4200 | 0.6224 | 0.7020 | 0.7654 | 0.7581 | 0.7590 | |
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| 0.2196 | 5.0 | 5250 | 0.7572 | 0.6954 | 0.7742 | 0.7557 | 0.7568 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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