---
language:
- ne
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- openslr/slr43
metrics:
- wer
model-index:
- name: Whisper small nepali - Rikesh Silwal
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: slr43
      type: openslr/slr43
      args: 'config: ne, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 33.719892952720784
---

<!-- 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. -->

# Whisper small nepali - Rikesh Silwal

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co./openai/whisper-small) on the slr43 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3583
- Wer: 33.7199

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0061        | 9.62  | 1000 | 0.3096          | 36.4853 |
| 0.0001        | 19.23 | 2000 | 0.3306          | 34.2551 |
| 0.0           | 28.85 | 3000 | 0.3525          | 33.5712 |
| 0.0           | 38.46 | 4000 | 0.3583          | 33.7199 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2