---
library_name: transformers
license: mit
base_model: ai4bharat/indic-bert
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_model014
  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. -->

# populism_model014

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: 0.5646
- Accuracy: 0.9717
- 1-f1: 0.3
- 1-recall: 0.2143
- 1-precision: 0.5
- Balanced Acc: 0.6040

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1   | 1-recall | 1-precision | Balanced Acc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.403         | 1.0   | 124  | 0.6092          | 0.9706   | 0.1714 | 0.1071   | 0.4286      | 0.5515       |
| 0.1578        | 2.0   | 248  | 0.4444          | 0.9737   | 0.4583 | 0.3929   | 0.55        | 0.6917       |
| 0.2256        | 3.0   | 372  | 0.5646          | 0.9717   | 0.3    | 0.2143   | 0.5         | 0.6040       |


### Framework versions

- Transformers 4.49.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0