---
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-hate-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-hate-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: 0.1222
- Accuracy: 0.9732
- Precision: 0.9733
- Recall: 0.9732
- F1: 0.9732

## 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: 16
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.6323        | 1.0   | 61   | 0.6216          | 0.6819   | 0.6951    | 0.6816 | 0.6762 |
| 0.6538        | 2.0   | 122  | 0.6064          | 0.6843   | 0.7260    | 0.6849 | 0.6695 |
| 0.478         | 3.0   | 183  | 0.6003          | 0.7060   | 0.7076    | 0.7059 | 0.7054 |
| 0.3915        | 4.0   | 244  | 0.5929          | 0.7373   | 0.748     | 0.7376 | 0.7346 |
| 0.3288        | 5.0   | 305  | 0.6091          | 0.7470   | 0.7560    | 0.7472 | 0.7448 |
| 0.2425        | 6.0   | 366  | 0.6779          | 0.7301   | 0.7344    | 0.7300 | 0.7288 |
| 0.1878        | 7.0   | 427  | 0.6804          | 0.7422   | 0.7423    | 0.7422 | 0.7421 |
| 0.1156        | 8.0   | 488  | 0.7229          | 0.7614   | 0.7616    | 0.7615 | 0.7614 |
| 0.1454        | 9.0   | 549  | 0.8009          | 0.7494   | 0.7528    | 0.7493 | 0.7485 |
| 0.1152        | 10.0  | 610  | 0.8109          | 0.7566   | 0.7571    | 0.7566 | 0.7565 |


### Framework versions

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