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perspective-toxic-bert
meghanagottapu/perspective-toxic-bert
perspective-toxic-bert is a machine learning model from meghanagottapu. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Apr 29, 2026
- Updated
- Apr 29, 2026
- SHA
- f80c9c09
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
perspective-toxic-bert
This model is a fine-tuned version of unitary/toxic-bert on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4656
- Tox Mse: 0.0239
- Tox Auc: 0.9631
- Dir Accuracy: 0.8345
- Dir F1 Macro: 0.5567
- Dir F1 Weighted: 0.8714
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.06
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Tox Mse | Tox Auc | Dir Accuracy | Dir F1 Macro | Dir F1 Weighted |
|---|---|---|---|---|---|---|---|---|
| 0.6404 | 1.0 | 997 | 0.4656 | 0.0239 | 0.9631 | 0.8345 | 0.5567 | 0.8714 |
Framework versions
- Transformers 5.7.0
- Pytorch 2.11.0+cu130
- Datasets 4.8.5
- Tokenizers 0.22.2
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Apr 29, 2026
- Updated
- Apr 29, 2026