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update model card README.md
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README.md
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license:
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---
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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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metrics:
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- accuracy
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- f1
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- precision
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- recall
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model-index:
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- name: toxicity-target-classification
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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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# toxicity-target-classification
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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: 0.6110
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- Accuracy: 0.6864
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- F1: 0.6872
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- Precision: 0.6882
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- Recall: 0.6864
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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: 4.174021560583183e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 1993
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- optimizer: Adam with betas=(0.9360294728287728,0.9974781444436187) and epsilon=8.016624612627008e-07
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- lr_scheduler_type: linear
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- num_epochs: 30
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- label_smoothing_factor: 0.09936835309930625
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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| 0.633 | 1.0 | 537 | 0.6040 | 0.6919 | 0.5805 | 0.6351 | 0.6919 |
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| 0.5915 | 2.0 | 1074 | 0.6110 | 0.6864 | 0.6872 | 0.6882 | 0.6864 |
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| 0.4584 | 3.0 | 1611 | 0.7104 | 0.6933 | 0.6606 | 0.6605 | 0.6933 |
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| 0.3564 | 4.0 | 2148 | 0.9816 | 0.6168 | 0.6307 | 0.6671 | 0.6168 |
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### Framework versions
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- Transformers 4.26.0
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- Pytorch 1.10.2+cu113
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- Datasets 2.9.0
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- Tokenizers 0.13.2
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