---
library_name: transformers
license: mit
base_model: ai4bharat/indic-bert
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: Paraphrase_indicBERT_onfull_FT3
  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. -->

# Paraphrase_indicBERT_onfull_FT3

This model is a fine-tuned version of [ai4bharat/indic-bert](https://huggingface.co/ai4bharat/indic-bert) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0320
- Accuracy: 0.789
- F1: 0.7885

## 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: 1.4638638566821256e-05
- train_batch_size: 32
- eval_batch_size: 64
- 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: 14

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.5707        | 1.0   | 157  | 0.5842          | 0.6895   | 0.6630 |
| 0.4831        | 2.0   | 314  | 0.5444          | 0.7435   | 0.7420 |
| 0.4363        | 3.0   | 471  | 0.4700          | 0.775    | 0.7730 |
| 0.3548        | 4.0   | 628  | 0.4781          | 0.7765   | 0.7763 |
| 0.2468        | 5.0   | 785  | 0.5416          | 0.786    | 0.7858 |
| 0.2046        | 6.0   | 942  | 0.6293          | 0.7775   | 0.7768 |
| 0.127         | 7.0   | 1099 | 0.6558          | 0.7815   | 0.7802 |
| 0.1042        | 8.0   | 1256 | 0.9524          | 0.742    | 0.7381 |
| 0.0653        | 9.0   | 1413 | 1.0619          | 0.7485   | 0.7450 |
| 0.0253        | 10.0  | 1570 | 1.0320          | 0.789    | 0.7885 |
| 0.0405        | 11.0  | 1727 | 1.1028          | 0.7795   | 0.7794 |
| 0.0106        | 12.0  | 1884 | 1.1150          | 0.784    | 0.7840 |
| 0.0098        | 13.0  | 2041 | 1.1362          | 0.785    | 0.7850 |
| 0.0331        | 14.0  | 2198 | 1.1453          | 0.785    | 0.7850 |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0