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update model card README.md
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README.md
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---
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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-type-detection
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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-type-detection
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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: 2.2337
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- Accuracy: 0.4214
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- F1: 0.7645
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- Precision: 0.8180
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- Recall: 0.7230
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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: 7.044186985160909e-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=(0.9339215524915885,0.9916979096990963) and epsilon=3.4435900142455904e-07
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- lr_scheduler_type: linear
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- num_epochs: 30
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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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| 1.1107 | 1.0 | 534 | 0.9282 | 0.2823 | 0.6762 | 0.7419 | 0.6630 |
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| 0.8974 | 2.0 | 1068 | 0.8605 | 0.2754 | 0.6324 | 0.7759 | 0.5913 |
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| 0.7436 | 3.0 | 1602 | 1.0151 | 0.3150 | 0.6870 | 0.7828 | 0.6512 |
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| 0.644 | 4.0 | 2136 | 1.1455 | 0.3519 | 0.7114 | 0.7857 | 0.6865 |
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| 0.4704 | 5.0 | 2670 | 1.4827 | 0.3387 | 0.7109 | 0.7814 | 0.6843 |
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| 0.3316 | 6.0 | 3204 | 1.6275 | 0.3602 | 0.7217 | 0.8020 | 0.6816 |
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| 0.2717 | 7.0 | 3738 | 2.2337 | 0.4214 | 0.7645 | 0.8180 | 0.7230 |
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| 0.231 | 8.0 | 4272 | 2.0275 | 0.3651 | 0.7194 | 0.8271 | 0.6528 |
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| 0.197 | 9.0 | 4806 | 1.9878 | 0.4033 | 0.7409 | 0.8240 | 0.6812 |
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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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