---
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-profanity-mr
  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-profanity-mr

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: 0.4716
- Accuracy: 0.9035
- Precision: 0.4517
- Recall: 0.5
- F1: 0.4746

## 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     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.5063        | 0.9836 | 30   | 0.4867          | 0.8819   | 0.4410    | 0.5    | 0.4686 |
| 0.3827        | 2.0    | 61   | 0.3841          | 0.8819   | 0.4410    | 0.5    | 0.4686 |
| 0.331         | 2.9836 | 91   | 0.3633          | 0.8819   | 0.4410    | 0.5    | 0.4686 |
| 0.323         | 4.0    | 122  | 0.3648          | 0.8819   | 0.4410    | 0.5    | 0.4686 |
| 0.295         | 4.9836 | 152  | 0.3657          | 0.8819   | 0.4410    | 0.5    | 0.4686 |
| 0.3048        | 6.0    | 183  | 0.3668          | 0.8819   | 0.4410    | 0.5    | 0.4686 |
| 0.3168        | 6.9836 | 213  | 0.3667          | 0.8819   | 0.4410    | 0.5    | 0.4686 |
| 0.3112        | 8.0    | 244  | 0.3666          | 0.8819   | 0.4410    | 0.5    | 0.4686 |
| 0.2971        | 8.9836 | 274  | 0.3663          | 0.8819   | 0.4410    | 0.5    | 0.4686 |
| 0.3009        | 9.8361 | 300  | 0.3662          | 0.8819   | 0.4410    | 0.5    | 0.4686 |


### Framework versions

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