Whisper Medium Indonesian
This model is a fine-tuned version of openai/whisper-medium on the Indonesian mozilla-foundation/common_voice_11_0, magic_data, titml and google/fleurs dataset. It achieves the following results:
CV11 test split:
- Loss: 0.0698
- Wer: 3.8274
Google/fleurs test split:
- Wer: 9.74
Usage
from transformers import pipeline
transcriber = pipeline(
"automatic-speech-recognition",
model="cahya/whisper-medium-id"
)
transcriber.model.config.forced_decoder_ids = (
transcriber.tokenizer.get_decoder_prompt_ids(
language="id"
task="transcribe"
)
)
transcription = transcriber("my_audio_file.mp3")
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-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0427 | 0.33 | 1000 | 0.0664 | 4.3807 |
| 0.042 | 0.66 | 2000 | 0.0658 | 3.9426 |
| 0.0265 | 0.99 | 3000 | 0.0657 | 3.8274 |
| 0.0211 | 1.32 | 4000 | 0.0679 | 3.8366 |
| 0.0212 | 1.66 | 5000 | 0.0682 | 3.8412 |
| 0.0206 | 1.99 | 6000 | 0.0683 | 3.8689 |
| 0.0166 | 2.32 | 7000 | 0.0711 | 3.9657 |
| 0.0095 | 2.65 | 8000 | 0.0717 | 3.9980 |
| 0.0122 | 2.98 | 9000 | 0.0714 | 3.9795 |
| 0.0049 | 3.31 | 10000 | 0.0720 | 3.9887 |
Evaluation
We evaluated the model using the test split of two datasets, the Common Voice 11 and the Google Fleurs. As Whisper can transcribe casing and punctuation, we also evaluate its performance using raw and normalized text. (lowercase + removal of punctuations). The results are as follows:
Common Voice 11
| WER | |
|---|---|
| cahya/whisper-medium-id | 3.83 |
| openai/whisper-medium | 12.62 |
Google/Fleurs
| WER | |
|---|---|
| cahya/whisper-medium-id | 9.74 |
| cahya/whisper-medium-id + text normalization | tbc |
| openai/whisper-medium | 10.2 |
| openai/whisper-medium + text normalization | tbc |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2