---
library_name: transformers
language:
- ne
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
datasets:
- kiranpantha/OpenSLR54-Balanced-Nepali
metrics:
- wer
model-index:
- name: Whisper Large v3 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: 18.72503840245776
---

<!-- 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 Large v3 Turbo Nepali - Kiran Pantha

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the OpenSLR54 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0876
- Wer: 18.7250
- Cer: 4.4861

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.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 | Cer     | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:-------:|:---------------:|:-------:|
| 0.2266        | 0.1200 | 300  | 11.9034 | 0.2345          | 44.7619 |
| 0.208         | 0.2399 | 600  | 11.3157 | 0.2132          | 41.1060 |
| 0.185         | 0.3599 | 900  | 9.4204  | 0.1753          | 35.6068 |
| 0.1567        | 0.4798 | 1200 | 8.8596  | 0.1634          | 33.9324 |
| 0.1411        | 0.5998 | 1500 | 8.7004  | 0.1523          | 33.0568 |
| 0.1377        | 0.7197 | 1800 | 7.3120  | 0.1371          | 29.7849 |
| 0.1147        | 0.8397 | 2100 | 7.0010  | 0.1332          | 27.7112 |
| 0.1116        | 0.9596 | 2400 | 6.5798  | 0.1212          | 26.3287 |
| 0.0757        | 1.0796 | 2700 | 6.1268  | 0.1193          | 24.7773 |
| 0.0609        | 1.1995 | 3000 | 5.8991  | 0.1154          | 24.6237 |
| 0.0612        | 1.3195 | 3300 | 5.2599  | 0.1091          | 22.0737 |
| 0.0627        | 1.4394 | 3600 | 5.3579  | 0.1045          | 21.6283 |
| 0.0582        | 1.5594 | 3900 | 5.1938  | 0.0995          | 21.5054 |
| 0.0551        | 1.6793 | 4200 | 4.7947  | 0.0956          | 19.8771 |
| 0.052         | 1.7993 | 4500 | 4.5473  | 0.0897          | 19.1244 |
| 0.0438        | 1.9192 | 4800 | 4.4861  | 0.0876          | 18.7250 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cxx11.abi
- Datasets 3.2.0
- Tokenizers 0.21.0