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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: toxic-comment-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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# toxic-comment-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: 0.5590 |
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- Accuracy: 0.8578 |
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- F1: 0.8580 |
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- Precision: 0.8594 |
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- Recall: 0.8578 |
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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: 3.255788747459486e-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=(0.8445637934160373,0.8338816842140165) and epsilon=2.527092625455385e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 30 |
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- label_smoothing_factor: 0.07158711257743958 |
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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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| 0.4422 | 1.0 | 1408 | 0.4197 | 0.8466 | 0.8470 | 0.8505 | 0.8466 | |
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| 0.3566 | 2.0 | 2816 | 0.4724 | 0.8413 | 0.8394 | 0.8453 | 0.8413 | |
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| 0.3135 | 3.0 | 4224 | 0.4801 | 0.8447 | 0.8434 | 0.8470 | 0.8447 | |
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| 0.2638 | 4.0 | 5632 | 0.5590 | 0.8578 | 0.8580 | 0.8594 | 0.8578 | |
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| 0.2314 | 5.0 | 7040 | 0.5605 | 0.8491 | 0.8487 | 0.8489 | 0.8491 | |
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| 0.2221 | 6.0 | 8448 | 0.6369 | 0.8416 | 0.8414 | 0.8414 | 0.8416 | |
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| 0.1939 | 7.0 | 9856 | 0.6518 | 0.8400 | 0.8402 | 0.8405 | 0.8400 | |
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| 0.2015 | 8.0 | 11264 | 0.6042 | 0.8462 | 0.8457 | 0.8465 | 0.8462 | |
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| 0.1989 | 9.0 | 12672 | 0.6236 | 0.8500 | 0.8496 | 0.8499 | 0.8500 | |
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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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