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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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base_model: neuralmind/bert-base-portuguese-cased |
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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: hate_BERTimbau_v1 |
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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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# hate_BERTimbau_v1 |
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This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0345 |
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- Precision: 0.7690 |
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- Recall: 0.7690 |
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- F1: 0.7690 |
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- Accuracy: 0.7690 |
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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: 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: 6 |
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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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| 0.5301 | 1.0 | 284 | 0.5012 | 0.7443 | 0.7443 | 0.7443 | 0.7443 | |
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| 0.4174 | 2.0 | 568 | 0.4574 | 0.7725 | 0.7725 | 0.7725 | 0.7725 | |
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| 0.2942 | 3.0 | 852 | 0.5691 | 0.7760 | 0.7760 | 0.7760 | 0.7760 | |
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| 0.1929 | 4.0 | 1136 | 0.7652 | 0.7672 | 0.7672 | 0.7672 | 0.7672 | |
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| 0.1283 | 5.0 | 1420 | 0.9161 | 0.7601 | 0.7601 | 0.7601 | 0.7601 | |
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| 0.0966 | 6.0 | 1704 | 1.0345 | 0.7690 | 0.7690 | 0.7690 | 0.7690 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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