---
library_name: transformers
language:
- ne
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- kiranpantha/OpenSLR54-Whisper
metrics:
- wer
model-index:
- name: Whisper Medium 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: 21.99074074074074
---

<!-- 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 Medium Nepali - Kiran Pantha

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the OpenSLR54 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1608
- Wer: 21.9907
- Cer: 5.3068

## 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 | Cer     | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:-------:|:---------------:|:-------:|
| 0.2877        | 0.3597 | 300  | 13.1055 | 0.2588          | 48.6574 |
| 0.1865        | 0.7194 | 600  | 10.0741 | 0.2052          | 39.9537 |
| 0.1155        | 1.0791 | 900  | 8.1217  | 0.1633          | 31.8981 |
| 0.0992        | 1.4388 | 1200 | 7.6923  | 0.1577          | 30.6250 |
| 0.094         | 1.7986 | 1500 | 7.1969  | 0.1418          | 28.3796 |
| 0.0454        | 2.1583 | 1800 | 6.7308  | 0.1472          | 26.6898 |
| 0.0333        | 2.5180 | 2100 | 6.6353  | 0.1512          | 27.0602 |
| 0.0446        | 2.8777 | 2400 | 6.25    | 0.1409          | 25.5556 |
| 0.0204        | 3.2374 | 2700 | 6.5399  | 0.1513          | 25.8796 |
| 0.016         | 3.5971 | 3000 | 5.9674  | 0.1560          | 24.8380 |
| 0.0166        | 3.9568 | 3300 | 6.0592  | 0.1573          | 25.0926 |
| 0.0052        | 4.3165 | 3600 | 5.7802  | 0.1566          | 23.3796 |
| 0.0068        | 4.6763 | 3900 | 5.5233  | 0.1544          | 22.7083 |
| 0.0013        | 5.0360 | 4200 | 5.4756  | 0.1568          | 22.7546 |
| 0.001         | 5.3957 | 4500 | 0.1606  | 22.0139         | 5.3178  |
| 0.0017        | 5.7554 | 4800 | 0.1608  | 21.9907         | 5.3068  |


### Framework versions

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