metadata
language:
- id
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
- magic_data
- TITML
metrics:
- wer
model-index:
- name: Whisper Medium 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: 3.8273540533062804
Whisper Medium Indonesian
This model is a fine-tuned version of openai/whisper-medium on the mozilla-foundation/common_voice_11_0, magic_data, titml id dataset. It achieves the following results on the evaluation set:
- Loss: 0.0698
- Wer: 3.8274
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-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 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2