Whisper Small Khmer
This model is a fine-tuned version of openai/whisper-small on a Khmer ASR dataset. It achieves the following results on the evaluation set:
- Loss: 0.0776
- WER: 78.5976
Model description
Fine-tuned for automatic speech recognition (ASR) in Khmer using a combination of public and custom datasets.
Intended uses & limitations
More information needed
Training and evaluation data
Includes:
- 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
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: AdamW (betas=(0.9, 0.999), eps=1e-08)
- lr_scheduler_type: constant
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10
- max_steps: 56940
- logging_steps: 500
- save_steps: 500
- eval_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | WER |
|---|---|---|---|---|
| 0.235 | 1.0 | 5694 | 0.1025 | 80.7038 |
| 0.0872 | 2.0 | 11388 | 0.0852 | 80.3682 |
| 0.0636 | 3.0 | 17082 | 0.0789 | 79.8482 |
| 0.0494 | 4.0 | 22776 | 0.0776 | 78.5976 |
Framework versions
- Transformers 4.51.3
- PyTorch 2.5.1+cu121
- Datasets 3.5.1
- Tokenizers 0.21.0