---
language:
- km
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- openslr
metrics:
- wer
model-index:
- name: Whisper Small Km - Kak Soky
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: SLR42
      type: openslr
      args: 'config: km, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 35.665399239543724
---

<!-- 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 Km - Kak Soky

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the SLR42 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1471
- Wer: 35.6654

## Model description

The model was fine-tuned on both encoder-decoder of transformer-based.

## Intended uses & limitations

The training data is limited, thus the performance is also limited to only reading speech and a limited domain (tourism).

## Training and evaluation data

The training and evaluation data was split in a 9:1 ratio from Google Text-to-speech corpus.

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 2
- eval_batch_size: 4
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3639        | 0.76  | 1000 | 0.3452          | 71.9392 |
| 0.1553        | 1.53  | 2000 | 0.2025          | 49.0494 |
| 0.0565        | 2.29  | 3000 | 0.1664          | 39.9240 |
| 0.0334        | 3.06  | 4000 | 0.1471          | 35.6654 |


### Framework versions

- Transformers 4.25.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.7.0
- Tokenizers 0.13.2