---
library_name: transformers
language:
- np
base_model: dexhrestha/Nepali-DistilBERT
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: Nepali-BERT-devangari-sentiment
  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. -->

# Nepali-BERT-devangari-sentiment

This model is a fine-tuned version of [dexhrestha/Nepali-DistilBERT](https://huggingface.co/dexhrestha/Nepali-DistilBERT) on the Custom Devangari Datasets dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5347
- Accuracy: 0.8403
- F1: 0.4837
- Precision: 0.3875
- Recall: 0.6435

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.5776        | 1.0   | 1189 | 0.5874          | 0.8373   | 0.4543 | 0.3725    | 0.5823 |
| 0.4707        | 2.0   | 2378 | 0.5347          | 0.8403   | 0.4837 | 0.3875    | 0.6435 |
| 0.3921        | 3.0   | 3567 | 0.6306          | 0.8530   | 0.4732 | 0.4057    | 0.5675 |
| 0.3146        | 4.0   | 4756 | 0.8935          | 0.8719   | 0.4673 | 0.4526    | 0.4831 |
| 0.248         | 5.0   | 5945 | 1.1782          | 0.8776   | 0.4582 | 0.4720    | 0.4451 |
| 0.1978        | 6.0   | 7134 | 1.2942          | 0.8648   | 0.4687 | 0.4316    | 0.5127 |
| 0.1504        | 7.0   | 8323 | 1.5298          | 0.8663   | 0.4609 | 0.4339    | 0.4916 |
| 0.1259        | 8.0   | 9512 | 1.6731          | 0.8761   | 0.4432 | 0.4642    | 0.4241 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1