---
library_name: transformers
license: cc-by-4.0
base_model: l3cube-pune/indic-sentence-bert-nli
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: indic-sentence-bert-nli-hinglish-binary
  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-sentence-bert-nli-hinglish-binary

This model is a fine-tuned version of [l3cube-pune/indic-sentence-bert-nli](https://huggingface.co/l3cube-pune/indic-sentence-bert-nli) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5934
- Accuracy: 0.6987
- Precision: 0.6929
- Recall: 0.6155
- F1: 0.6125

## 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: 4
- total_train_batch_size: 128
- 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     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.663         | 0.9709 | 25   | 0.6551          | 0.6376   | 0.3188    | 0.5    | 0.3894 |
| 0.6284        | 1.9806 | 51   | 0.6314          | 0.6676   | 0.7906    | 0.5430 | 0.4785 |
| 0.6266        | 2.9903 | 77   | 0.6725          | 0.5095   | 0.6373    | 0.5975 | 0.4974 |
| 0.6261        | 4.0    | 103  | 0.6008          | 0.7112   | 0.7124    | 0.6307 | 0.6311 |
| 0.6202        | 4.9709 | 128  | 0.6025          | 0.7057   | 0.7005    | 0.6264 | 0.6265 |
| 0.5987        | 5.9806 | 154  | 0.5907          | 0.7112   | 0.7216    | 0.6258 | 0.6236 |
| 0.5856        | 6.9903 | 180  | 0.5818          | 0.7193   | 0.7253    | 0.6404 | 0.6427 |
| 0.5753        | 8.0    | 206  | 0.5804          | 0.7166   | 0.7502    | 0.6252 | 0.6201 |
| 0.5416        | 8.9709 | 231  | 0.5667          | 0.7221   | 0.7424    | 0.6376 | 0.6378 |
| 0.5419        | 9.7087 | 250  | 0.5599          | 0.7330   | 0.7439    | 0.6575 | 0.6632 |


### Framework versions

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