---
library_name: transformers
language:
- ne
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- kiranpantha/OpenSLR54-Balanced-Nepali
metrics:
- wer
model-index:
- name: Whisper Tiny Nepali - Kiran Pantha
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: OpenSLR54
      type: kiranpantha/OpenSLR54-Balanced-Nepali
      config: default
      split: test
      args: 'config: ne, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 53.726851851851855
---

<!-- 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 Tiny Nepali - Kiran Pantha

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co./openai/whisper-tiny) on the OpenSLR54 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2933
- Wer: 53.7269
- Cer: 16.1186

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     | Cer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|
| 0.8115        | 0.3597 | 300  | 0.7467          | 92.9167 | 34.9897 |
| 0.4976        | 0.7194 | 600  | 0.4963          | 79.2130 | 26.2625 |
| 0.3874        | 1.0791 | 900  | 0.4198          | 71.5046 | 22.6696 |
| 0.3422        | 1.4388 | 1200 | 0.3797          | 67.5926 | 20.8896 |
| 0.3179        | 1.7986 | 1500 | 0.3467          | 63.9120 | 19.3959 |
| 0.2451        | 2.1583 | 1800 | 0.3299          | 62.1528 | 18.6950 |
| 0.2167        | 2.5180 | 2100 | 0.3224          | 60.6713 | 18.3977 |
| 0.2428        | 2.8777 | 2400 | 0.3085          | 59.6528 | 17.6196 |
| 0.1862        | 3.2374 | 2700 | 0.3057          | 57.6620 | 16.9113 |
| 0.1795        | 3.5971 | 3000 | 0.3007          | 57.5231 | 16.7792 |
| 0.1758        | 3.9568 | 3300 | 0.2935          | 55.8565 | 16.5297 |
| 0.1496        | 4.3165 | 3600 | 0.2960          | 55.8796 | 16.3792 |
| 0.156         | 4.6763 | 3900 | 0.2940          | 55.4398 | 16.4819 |
| 0.1235        | 5.0360 | 4200 | 0.2915          | 54.4444 | 16.0085 |
| 0.1311        | 5.3957 | 4500 | 0.2936          | 54.4676 | 16.2801 |
| 0.1136        | 5.7554 | 4800 | 0.2933          | 53.7269 | 16.1186 |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cxx11.abi
- Datasets 3.2.0
- Tokenizers 0.20.3