whisper-small-khmer – AI Model by PhanithLIM | AlphaNeural AI

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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