metadata
language:
- id
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
- magic_data
- titml
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Tiny Indonesian
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_11_0 id
type: mozilla-foundation/common_voice_11_0
config: id
split: test
metrics:
- name: Wer
type: wer
value: 18.28368532693904
Whisper Tiny Indonesian
This model is a fine-tuned version of openai/whisper-tiny on the mozilla-foundation/common_voice_11_0, magic_data, titml and google/fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 0.2409
- Wer: 18.2837
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: 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 |
|---|---|---|---|---|
| 0.4103 | 0.66 | 1000 | 0.3802 | 27.0497 |
| 0.2682 | 1.32 | 2000 | 0.3223 | 22.9365 |
| 0.2381 | 1.99 | 3000 | 0.2884 | 20.8245 |
| 0.1606 | 2.65 | 4000 | 0.2727 | 20.1928 |
| 0.1246 | 3.31 | 5000 | 0.2596 | 18.9984 |
| 0.1344 | 3.97 | 6000 | 0.2482 | 18.7540 |
| 0.0975 | 4.63 | 7000 | 0.2471 | 18.6388 |
| 0.0916 | 5.29 | 8000 | 0.2436 | 18.9615 |
| 0.0854 | 5.96 | 9000 | 0.2413 | 18.3114 |
| 0.0812 | 6.62 | 10000 | 0.2409 | 18.2837 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2