---
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-binary
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# indic-sentence-bert-nli-roman-urdu-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: 0.2789
- Accuracy: 0.9061
- Precision: 0.9058
- Recall: 0.9055
- F1: 0.9057

## 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     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.4984        | 0.9912 | 56   | 0.4611          | 0.8452   | 0.8486    | 0.8489 | 0.8452 |
| 0.3582        | 2.0    | 113  | 0.3373          | 0.8826   | 0.8843    | 0.8802 | 0.8816 |
| 0.2724        | 2.9912 | 169  | 0.2869          | 0.8901   | 0.8894    | 0.8901 | 0.8897 |
| 0.2093        | 4.0    | 226  | 0.2754          | 0.8926   | 0.8922    | 0.8920 | 0.8921 |
| 0.1622        | 4.9912 | 282  | 0.2980          | 0.8989   | 0.9016    | 0.8961 | 0.8978 |
| 0.1235        | 6.0    | 339  | 0.3167          | 0.8889   | 0.8883    | 0.8884 | 0.8884 |
| 0.1125        | 6.9912 | 395  | 0.3369          | 0.8939   | 0.8973    | 0.8907 | 0.8926 |
| 0.0811        | 8.0    | 452  | 0.3535          | 0.8914   | 0.8906    | 0.8918 | 0.8911 |
| 0.0797        | 8.9912 | 508  | 0.3833          | 0.8914   | 0.8919    | 0.8898 | 0.8906 |
| 0.0585        | 9.9115 | 560  | 0.3809          | 0.8926   | 0.8924    | 0.8918 | 0.8920 |


### Framework versions

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