---
library_name: transformers
license: mit
base_model: ai4bharat/indic-bert
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: indic-bert-roman-urdu-fine-grained
  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. -->

# indic-bert-roman-urdu-fine-grained

This model is a fine-tuned version of [ai4bharat/indic-bert](https://huggingface.co/ai4bharat/indic-bert) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8501
- Accuracy: 0.7678
- Precision: 0.6945
- Recall: 0.6537
- F1: 0.6720

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.1237        | 1.0   | 113  | 1.0947          | 0.5342   | 0.1068    | 0.2    | 0.1393 |
| 0.9606        | 2.0   | 226  | 0.8776          | 0.6689   | 0.4456    | 0.3188 | 0.2779 |
| 0.7784        | 3.0   | 339  | 0.6443          | 0.7896   | 0.7017    | 0.6830 | 0.6899 |
| 0.5626        | 4.0   | 452  | 0.5167          | 0.8302   | 0.7561    | 0.7371 | 0.7422 |
| 0.5613        | 5.0   | 565  | 0.4285          | 0.8634   | 0.7931    | 0.7849 | 0.7850 |
| 0.4232        | 6.0   | 678  | 0.3543          | 0.8867   | 0.8295    | 0.8072 | 0.8155 |
| 0.3376        | 7.0   | 791  | 0.2546          | 0.9293   | 0.8850    | 0.8757 | 0.8802 |
| 0.2759        | 8.0   | 904  | 0.2079          | 0.9469   | 0.9085    | 0.9132 | 0.9103 |
| 0.2029        | 9.0   | 1017 | 0.1564          | 0.9606   | 0.9370    | 0.9276 | 0.9322 |
| 0.137         | 10.0  | 1130 | 0.1364          | 0.9685   | 0.9558    | 0.9399 | 0.9477 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0