---
library_name: transformers
language:
- np
base_model: RoBERTa
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: RoBERTa-devangari-script-classification
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# RoBERTa-devangari-script-classification

This model is a fine-tuned version of [RoBERTa](https://huggingface.co/RoBERTa) on the Custom Devangari Datasets dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0329
- Accuracy: 0.9935
- F1: 0.9935
- Precision: 0.9935
- Recall: 0.9935

## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.2337        | 0.9997 | 1638 | 0.0603          | 0.9874   | 0.9874 | 0.9875    | 0.9874 |
| 0.0513        | 2.0    | 3277 | 0.0387          | 0.9919   | 0.9919 | 0.9919    | 0.9919 |
| 0.0252        | 2.9991 | 4914 | 0.0329          | 0.9935   | 0.9935 | 0.9935    | 0.9935 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1