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

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: 1.1108
- Accuracy: 0.6896
- Precision: 0.2983
- Recall: 0.2872
- F1: 0.2740

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.1508        | 1.0   | 93   | 1.2143          | 0.6216   | 0.1373    | 0.1440 | 0.1253 |
| 1.1999        | 2.0   | 186  | 1.1389          | 0.6337   | 0.1632    | 0.1656 | 0.1545 |
| 1.0445        | 3.0   | 279  | 1.0623          | 0.6815   | 0.2057    | 0.2219 | 0.2109 |
| 0.882         | 4.0   | 372  | 1.0181          | 0.6996   | 0.3264    | 0.3092 | 0.2976 |
| 0.7892        | 5.0   | 465  | 1.0408          | 0.7036   | 0.3327    | 0.3097 | 0.3011 |
| 0.7381        | 6.0   | 558  | 1.1007          | 0.7103   | 0.3317    | 0.3060 | 0.3057 |
| 0.6175        | 7.0   | 651  | 1.2323          | 0.7070   | 0.3241    | 0.3014 | 0.3037 |
| 0.49          | 8.0   | 744  | 1.2686          | 0.6956   | 0.4590    | 0.3093 | 0.3164 |
| 0.4576        | 9.0   | 837  | 1.3347          | 0.6761   | 0.3285    | 0.3200 | 0.3199 |
| 0.3436        | 10.0  | 930  | 1.3501          | 0.6673   | 0.3363    | 0.3167 | 0.3204 |


### Framework versions

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