---
library_name: transformers
license: mit
base_model: ai4bharat/indic-bert
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: guj-eng-code-switch-indic-bert-data2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# guj-eng-code-switch-indic-bert-data2

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: 0.1092
- Precision: 0.8989
- Recall: 0.9179
- F1: 0.9083
- Accuracy: 0.9729

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1859        | 1.0   | 250  | 0.1751          | 0.8527    | 0.8463 | 0.8495 | 0.9603   |
| 0.1184        | 2.0   | 500  | 0.1365          | 0.8785    | 0.8990 | 0.8886 | 0.9638   |
| 0.0726        | 3.0   | 750  | 0.1092          | 0.8989    | 0.9179 | 0.9083 | 0.9729   |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.9.0+cu126
- Datasets 4.4.1
- Tokenizers 0.22.1