metadata
language:
- id
license: apache-2.0
base_model: openai/whisper-small
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_9_0
metrics:
- wer
model-index:
- name: Whisper Small Indonesian
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_9_0 id
type: mozilla-foundation/common_voice_9_0
config: id
split: train
args: id
metrics:
- name: Wer
type: wer
value: 0.3947650718729886
Whisper Small Indonesian
This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_9_0 id dataset. It achieves the following results on the evaluation set:
- Loss: 0.0004
- Wer: 0.3948
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: 0.0001
- train_batch_size: 12
- eval_batch_size: 6
- 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: 5000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2264 | 2.38 | 1000 | 0.1836 | 14.9989 |
| 0.0873 | 4.75 | 2000 | 0.0633 | 5.0869 |
| 0.0236 | 7.13 | 3000 | 0.0262 | 1.8086 |
| 0.0068 | 9.5 | 4000 | 0.0062 | 0.6222 |
| 0.0002 | 11.88 | 5000 | 0.0004 | 0.3948 |
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3