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

# indic-bert-hate-mr

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: 0.2408
- Accuracy: 0.9226
- Precision: 0.9270
- Recall: 0.9225
- F1: 0.9224

## 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: 2
- total_train_batch_size: 32
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.6637        | 1.0   | 61   | 0.6441          | 0.6530   | 0.6780    | 0.6526 | 0.6400 |
| 0.678         | 2.0   | 122  | 0.6538          | 0.6386   | 0.6408    | 0.6387 | 0.6372 |
| 0.6422        | 3.0   | 183  | 0.6597          | 0.6410   | 0.6607    | 0.6405 | 0.6292 |
| 0.6281        | 4.0   | 244  | 0.6202          | 0.6578   | 0.6591    | 0.6579 | 0.6573 |
| 0.5374        | 5.0   | 305  | 0.6306          | 0.6723   | 0.6746    | 0.6721 | 0.6711 |
| 0.4418        | 6.0   | 366  | 0.7122          | 0.6795   | 0.6991    | 0.6799 | 0.6717 |
| 0.3981        | 7.0   | 427  | 0.7183          | 0.6602   | 0.6603    | 0.6602 | 0.6602 |
| 0.3054        | 8.0   | 488  | 0.8008          | 0.6867   | 0.6889    | 0.6869 | 0.6859 |
| 0.2445        | 9.0   | 549  | 0.9741          | 0.6578   | 0.6587    | 0.6577 | 0.6573 |
| 0.1882        | 10.0  | 610  | 0.9924          | 0.6723   | 0.6723    | 0.6723 | 0.6723 |


### Framework versions

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