---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny
datasets:
- PhanithLIM/ams-speech-dataset
- openslr/openslr
- google/fleurs
- PhanithLIM/kh-wmc
- PhanithLIM/wmc-international-news
- PhanithLIM/rfi-news-dataset
- PhanithLIM/aakanee-kh
- rinabuoy/khm-asr-open
- seanghay/khmer_grkpp_speech
- seanghay/khmer_mpwt_speech
- seanghay/km-speech-corpus
model-index:
- name: Khmer Whisper Small PhanithLIM
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Google Fleurs
      type: google/fleurs
      config: km_kh
      split: test
    metrics:
    - name: CER
      type: cer
      value: 22.511
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: WMC
      type: PhanithLIM/asr-wmc-evaluate
      split: test
    metrics:
    - name: CER
      type: cer
      value: 12.581
tags:
- generated_from_trainer
metrics:
- wer
---

<!-- 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-tiny-aug-7-may-lightning-v1

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1300
- Wer: 86.2590

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0747        | 1.0   | 712  | 0.4463          | 102.0236 |
| 0.3496        | 2.0   | 1424 | 0.2607          | 98.4686  |
| 0.2411        | 3.0   | 2136 | 0.2071          | 92.8878  |
| 0.1966        | 4.0   | 2848 | 0.1819          | 94.1085  |
| 0.1699        | 5.0   | 3560 | 0.1653          | 92.2555  |
| 0.1514        | 6.0   | 4272 | 0.1533          | 88.5561  |
| 0.1377        | 7.0   | 4984 | 0.1452          | 88.0289  |
| 0.1265        | 8.0   | 5696 | 0.1391          | 86.8913  |
| 0.117         | 9.0   | 6408 | 0.1331          | 87.4382  |
| 0.1089        | 10.0  | 7120 | 0.1300          | 86.2590  |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.7.0+cu128
- Datasets 3.5.1
- Tokenizers 0.21.1