---
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-roman-urdu-binary
  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-roman-urdu-binary

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: 0.3226
- Accuracy: 0.8832
- Precision: 0.8841
- Recall: 0.8857
- F1: 0.8831

## 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: 16
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 4
- 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     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.5453        | 0.9933 | 112  | 0.3860          | 0.8277   | 0.8311    | 0.8314 | 0.8277 |
| 1.0577        | 1.9933 | 224  | 0.2918          | 0.8777   | 0.8843    | 0.8731 | 0.8757 |
| 0.6143        | 2.9933 | 336  | 0.3023          | 0.8876   | 0.8871    | 0.8888 | 0.8874 |
| 0.2438        | 3.9933 | 448  | 0.6792          | 0.8652   | 0.8714    | 0.8606 | 0.8630 |
| 0.063         | 4.9933 | 560  | 0.7500          | 0.8789   | 0.8817    | 0.8758 | 0.8776 |
| 0.052         | 5.9933 | 672  | 0.8892          | 0.8777   | 0.8832    | 0.8735 | 0.8758 |
| 0.0005        | 6.9933 | 784  | 0.9423          | 0.8801   | 0.8863    | 0.8758 | 0.8783 |
| 0.0002        | 7.9933 | 896  | 0.8404          | 0.8752   | 0.8777    | 0.8722 | 0.8738 |
| 0.0           | 8.9933 | 1008 | 0.8774          | 0.8777   | 0.8823    | 0.8738 | 0.8760 |
| 0.0           | 9.9933 | 1120 | 0.8828          | 0.8777   | 0.8823    | 0.8738 | 0.8760 |


### Framework versions

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