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---
language:
- id
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Base 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
args: id
metrics:
- name: Wer
type: wer
value: 23.757262750161395
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Whisper Base Indonesian
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co./openai/whisper-base) on the mozilla-foundation/common_voice_11_0 id dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5101
- Wer: 23.7573
## 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: 2e-05
- train_batch_size: 64
- eval_batch_size: 32
- 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
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2041 | 4.95 | 500 | 0.3906 | 23.9140 |
| 0.015 | 9.9 | 1000 | 0.4619 | 24.3752 |
| 0.0032 | 14.85 | 1500 | 0.4901 | 23.7803 |
| 0.0015 | 19.8 | 2000 | 0.5101 | 23.7573 |
| 0.001 | 24.75 | 2500 | 0.5265 | 23.9786 |
| 0.0008 | 29.7 | 3000 | 0.5399 | 24.1216 |
| 0.0006 | 34.65 | 3500 | 0.5501 | 23.8956 |
| 0.0005 | 39.6 | 4000 | 0.5583 | 24.0570 |
| 0.0004 | 44.55 | 4500 | 0.5638 | 24.1815 |
| 0.0004 | 49.5 | 5000 | 0.5659 | 24.1492 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
|