---
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-roman-urdu-fine-grained
  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-roman-urdu-fine-grained

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: 0.7424
- Accuracy: 0.7858
- Precision: 0.7111
- Recall: 0.6798
- F1: 0.6906

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.1702        | 1.0   | 113  | 1.1398          | 0.5901   | 0.3936    | 0.3331 | 0.2566 |
| 0.9227        | 2.0   | 226  | 0.8477          | 0.7001   | 0.2670    | 0.3508 | 0.2990 |
| 0.8216        | 3.0   | 339  | 0.7744          | 0.7309   | 0.3829    | 0.4267 | 0.3918 |
| 0.6698        | 4.0   | 452  | 0.6684          | 0.7713   | 0.5727    | 0.5493 | 0.5269 |
| 0.6337        | 5.0   | 565  | 0.5499          | 0.8340   | 0.6059    | 0.6291 | 0.6115 |
| 0.5396        | 6.0   | 678  | 0.4947          | 0.8428   | 0.6067    | 0.6571 | 0.6247 |
| 0.469         | 7.0   | 791  | 0.4368          | 0.8756   | 0.7950    | 0.7254 | 0.7261 |
| 0.4571        | 8.0   | 904  | 0.3816          | 0.9105   | 0.8661    | 0.8083 | 0.8305 |
| 0.4099        | 9.0   | 1017 | 0.3544          | 0.9237   | 0.8699    | 0.8494 | 0.8558 |
| 0.3605        | 10.0  | 1130 | 0.3385          | 0.9256   | 0.8819    | 0.8436 | 0.8576 |


### Framework versions

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