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

# indic-bert-profanity-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: 0.3187
- Accuracy: 0.9035
- Precision: 0.4517
- Recall: 0.5
- F1: 0.4746

## 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     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.3272        | 0.9836 | 30   | 0.3721          | 0.8819   | 0.4410    | 0.5    | 0.4686 |
| 0.3332        | 2.0    | 61   | 0.3677          | 0.8819   | 0.4410    | 0.5    | 0.4686 |
| 0.3293        | 2.9836 | 91   | 0.3768          | 0.8819   | 0.4410    | 0.5    | 0.4686 |
| 0.3275        | 4.0    | 122  | 0.3612          | 0.8819   | 0.4410    | 0.5    | 0.4686 |
| 0.2919        | 4.9836 | 152  | 0.3752          | 0.8819   | 0.4410    | 0.5    | 0.4686 |
| 0.291         | 6.0    | 183  | 0.3618          | 0.8819   | 0.4410    | 0.5    | 0.4686 |
| 0.281         | 6.9836 | 213  | 0.3793          | 0.8819   | 0.4410    | 0.5    | 0.4686 |
| 0.2399        | 8.0    | 244  | 0.3854          | 0.8819   | 0.4410    | 0.5    | 0.4686 |
| 0.1822        | 8.9836 | 274  | 0.4216          | 0.8819   | 0.4410    | 0.5    | 0.4686 |
| 0.1354        | 9.8361 | 300  | 0.4200          | 0.8819   | 0.6938    | 0.5265 | 0.5229 |


### Framework versions

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