---
language:
- km
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- openslr
- google/fleurs

metrics:
- wer

model-index:
- name: Whisper Small Khmer - Seanghay Yath
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Google FLEURS
      type: google/fleurs
      config: km_kh
      split: all
    metrics:
    - name: Wer
      type: wer
      value: 1.0704381586245146
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Small Khmer - Seanghay Yath

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Google FLEURS & OpenSLR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4484
- Wer: 1.0704

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 6.25e-06
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 800
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.2052        | 3.33  | 1000 | 0.3582          | 1.0233 |
| 0.0465        | 6.67  | 2000 | 0.3129          | 1.0105 |
| 0.0089        | 10.0  | 3000 | 0.3977          | 1.0214 |
| 0.0016        | 13.33 | 4000 | 0.4484          | 1.0704 |


### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 1.12.1
- Datasets 2.11.1.dev0
- Tokenizers 0.13.3