---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-large
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: ModernBERT-large-profanity-mr
  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-large-profanity-mr

This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Accuracy: 1.0
- Precision: 1.0
- Recall: 1.0
- F1: 1.0

## 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: 128
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Use adamw_hf with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.6922        | 1.0    | 31   | 0.3749          | 0.8819   | 0.4410    | 0.5    | 0.4686 |
| 0.6034        | 2.0    | 62   | 0.3849          | 0.8819   | 0.4410    | 0.5    | 0.4686 |
| 0.4476        | 3.0    | 93   | 0.4496          | 0.8072   | 0.6147    | 0.6698 | 0.6305 |
| 0.2277        | 4.0    | 124  | 0.3633          | 0.8699   | 0.6384    | 0.5639 | 0.5788 |
| 0.0546        | 5.0    | 155  | 0.6659          | 0.8819   | 0.6947    | 0.5354 | 0.5385 |
| 0.0066        | 6.0    | 186  | 0.9790          | 0.8843   | 0.7195    | 0.5544 | 0.5688 |
| 0.0003        | 7.0    | 217  | 1.1011          | 0.8867   | 0.7584    | 0.5469 | 0.5573 |
| 0.0001        | 8.0    | 248  | 1.0485          | 0.8867   | 0.7469    | 0.5558 | 0.5712 |
| 0.0           | 9.0    | 279  | 1.0500          | 0.8867   | 0.7469    | 0.5558 | 0.5712 |
| 0.0           | 9.6885 | 300  | 1.0516          | 0.8867   | 0.7469    | 0.5558 | 0.5712 |


### Framework versions

- Transformers 4.48.2
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0