---
library_name: transformers
language:
- ne
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- generated_from_trainer
datasets:
- kiranpantha/OpenSLR54-Whisper
metrics:
- wer
model-index:
- name: Whisper Large v3 Turbo Nepali - Kiran Pantha
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: OpenSLR54
      type: kiranpantha/OpenSLR54-Whisper
      config: default
      split: test
      args: 'config: ne, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 23.63425925925926
---

<!-- 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-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the OpenSLR54 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1707
- Wer: 23.6343
- Cer: 5.4903

## 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     |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|
| 0.3073        | 0.3597 | 300  | 0.2895          | 53.2870 | 13.5643 |
| 0.2457        | 0.7194 | 600  | 0.2396          | 45.3704 | 11.6816 |
| 0.166         | 1.0791 | 900  | 0.2062          | 37.9167 | 9.6668  |
| 0.1477        | 1.4388 | 1200 | 0.1949          | 37.4306 | 9.3071  |
| 0.1284        | 1.7986 | 1500 | 0.1680          | 32.6620 | 8.3235  |
| 0.0745        | 2.1583 | 1800 | 0.1706          | 31.1574 | 7.5272  |
| 0.0701        | 2.5180 | 2100 | 0.1661          | 32.0370 | 7.7217  |
| 0.0777        | 2.8777 | 2400 | 0.1599          | 28.6111 | 7.1308  |
| 0.0455        | 3.2374 | 2700 | 0.1723          | 28.7037 | 7.0097  |
| 0.0375        | 3.5971 | 3000 | 0.1579          | 26.9444 | 6.3674  |
| 0.0374        | 3.9568 | 3300 | 0.1639          | 26.8981 | 6.2794  |
| 0.0171        | 4.3165 | 3600 | 0.1711          | 25.3241 | 6.2280  |
| 0.0219        | 4.6763 | 3900 | 0.1638          | 25.0    | 5.9307  |
| 0.0089        | 5.0360 | 4200 | 0.1635          | 24.5139 | 5.7435  |
| 0.0072        | 5.3957 | 4500 | 0.1717          | 24.1898 | 5.5711  |
| 0.0059        | 5.7554 | 4800 | 0.1707          | 23.6343 | 5.4903  |


### Framework versions

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