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---
language:
- id
license: apache-2.0
tags:
- automatic-speech-recognition
- hf-asr-leaderboard
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_8_0
metrics:
- wer
- cer
base_model: facebook/wav2vec2-xls-r-1b
model-index:
- name: wav2vec2-large-xls-r-1b-Indonesian
results:
- task:
type: automatic-speech-recognition
name: Speech Recognition
dataset:
name: Common Voice id
type: mozilla-foundation/common_voice_8_0
args: id
metrics:
- type: wer
value: 45.51
name: Test WER
- type: cer
value: 16.43
name: Test CER
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Robust Speech Event - Dev Data
type: speech-recognition-community-v2/dev_data
args: id
metrics:
- type: wer
value: 72.73
name: Test WER
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Robust Speech Event - Test Data
type: speech-recognition-community-v2/eval_data
args: id
metrics:
- type: wer
value: 79.29
name: Test WER
---
<!-- 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. -->
# wav2vec2-large-xls-r-1b-Indonesian
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9550
- Wer: 0.4551
- Cer: 0.1643
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 64
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 400
- num_epochs: 50
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 3.663 | 7.69 | 200 | 0.7898 | 0.6039 | 0.1848 |
| 0.7424 | 15.38 | 400 | 1.0215 | 0.5615 | 0.1924 |
| 0.4494 | 23.08 | 600 | 1.0901 | 0.5249 | 0.1932 |
| 0.5075 | 30.77 | 800 | 1.1013 | 0.5079 | 0.1935 |
| 0.4671 | 38.46 | 1000 | 1.1034 | 0.4916 | 0.1827 |
| 0.1928 | 46.15 | 1200 | 0.9550 | 0.4551 | 0.1643 |
### Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0
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