Whisper Small Hy 2 - Erik Mkrtchyan
This model is a fine-tuned version of openai/whisper-small on the Hy Generated Audio Data dataset. It achieves the following results on the evaluation set:
- Loss: 0.0999
- Wer: 22.7854
Model description
This model is based on OpenAI's Whisper Small and fine-tuned for Armenian using a combination of real and synthetic audio data. It is designed to transcribe Armenian speech into text.
Intended uses & limitations
Intended Uses:
- Armenian speech-to-text applications
- Research on ASR for low-resource languages
- Educational and experimental projects involving Whisper models
Limitations:
- May not generalize well to accents or noisy audio not represented in the training set
- he model may hallucinate text or produce inaccurate transcriptions, especially on unusual or out-of-distribution inputs, due to the inclusion of TTS-generated synthetic data in training.
Training and evaluation data
The dataset contains both real and high-quality synthetic Armenian speech clips.
Split(1) | # Clips | Duration (hours) |
---|---|---|
train |
9,300 | 13.53 |
test |
5,818 | 9.16 |
eval |
5,856 | 8.76 |
generated |
100,000 | 113.61 |
generated[2] |
137,419 | 173.76 |
Total duration: ~318 hours
Train set duration(train+generated#1+generated#2: ~300 hours
Test set duration(test+eval) ~18 hours
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.0516 | 0.4999 | 7709 | 0.1417 | 33.0858 |
0.0366 | 0.9999 | 15418 | 0.1139 | 27.4340 |
0.0275 | 1.4998 | 23127 | 0.1057 | 25.0415 |
0.0308 | 1.9997 | 30836 | 0.0981 | 23.7545 |
0.017 | 2.4997 | 38545 | 0.1016 | 23.2408 |
0.019 | 2.9996 | 46254 | 0.0999 | 22.7854 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.7.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1
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Evaluation results
- Wer on Hy Generated Audio Data with CV 20.0self-reported22.785