metadata
language:
- id
license: apache-2.0
base_model: openai/whisper-small
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
metrics:
- wer
model-index:
- name: Breeze DSW Indonesian - small
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_16_0 id
type: mozilla-foundation/common_voice_16_0
config: id
split: test
args: id
metrics:
- name: Wer
type: wer
value: 17.70632072867789
Breeze DSW Indonesian - small
This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_16_0 id dataset. It achieves the following results on the evaluation set:
- Loss: 0.3159
- Wer: 17.7063
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
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4199 | 0.1 | 100 | 0.3494 | 19.1600 |
| 0.282 | 1.04 | 200 | 0.3159 | 17.7063 |
| 0.1241 | 1.14 | 300 | 0.3291 | 18.5988 |
| 0.1232 | 2.09 | 400 | 0.3279 | 18.8886 |
| 0.064 | 3.03 | 500 | 0.3389 | 17.9133 |
| 0.0305 | 3.13 | 600 | 0.3557 | 18.4792 |
| 0.0282 | 4.08 | 700 | 0.3625 | 18.0559 |
| 0.0117 | 5.02 | 800 | 0.3699 | 18.2906 |
| 0.0079 | 5.12 | 900 | 0.3794 | 18.3596 |
| 0.0081 | 6.06 | 1000 | 0.3826 | 18.2906 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0