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---
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library_name: transformers
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license: apache-2.0
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base_model: answerdotai/ModernBERT-base
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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: modernbert_hate_speech_ft
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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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# modernbert_hate_speech_ft
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This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4457
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- Accuracy: 0.7954
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- F1: 0.7788
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- Precision: 0.7825
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- Recall: 0.7752
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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: 5e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.98) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 3
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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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| 0.4664 | 1.0 | 22519 | 0.4517 | 0.7919 | 0.7734 | 0.7829 | 0.7642 |
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| 0.4471 | 2.0 | 45038 | 0.4458 | 0.7952 | 0.7790 | 0.7815 | 0.7766 |
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| 0.4437 | 3.0 | 67557 | 0.4444 | 0.7959 | 0.7786 | 0.7852 | 0.7721 |
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### Framework versions
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- Transformers 4.49.0
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- Pytorch 2.6.0+cu126
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- Datasets 3.3.2
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- Tokenizers 0.21.0
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