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---

library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: modernbert_hate_speech_ft
  results: []
---


<!-- 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. -->

# modernbert_hate_speech_ft



This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on an unknown dataset.

It achieves the following results on the evaluation set:

- Loss: 0.4457

- Accuracy: 0.7954

- F1: 0.7788

- Precision: 0.7825

- Recall: 0.7752



## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.98) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3



### Training results



| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |

|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|

| 0.4664        | 1.0   | 22519 | 0.4517          | 0.7919   | 0.7734 | 0.7829    | 0.7642 |

| 0.4471        | 2.0   | 45038 | 0.4458          | 0.7952   | 0.7790 | 0.7815    | 0.7766 |

| 0.4437        | 3.0   | 67557 | 0.4444          | 0.7959   | 0.7786 | 0.7852    | 0.7721 |





### Framework versions



- Transformers 4.49.0

- Pytorch 2.6.0+cu126

- Datasets 3.3.2

- Tokenizers 0.21.0