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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_7_0
metrics:
- wer
- cer
model-index:
- name: wav2vec2-large-xls-r-300m-Indonesian
results:
- task:
type: automatic-speech-recognition
name: Speech Recognition
dataset:
type: mozilla-foundation/common_voice_7_0
name: Common Voice id
args: id
metrics:
- type: wer
value: 25.06
name: Test WER With LM
- type: cer
value: 6.5
name: Test CER With LM
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Dev Data
type: speech-recognition-community-v2/dev_data
args: id
metrics:
- name: Test WER
type: wer
value: 99.61
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Test Data
type: speech-recognition-community-v2/eval_data
args: id
metrics:
- name: Test WER
type: wer
value: 106.39
---
<!-- 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-300m-Indonesian
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4087
- Wer: 0.2461
- Cer: 0.0666
### 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 5.0788 | 4.26 | 200 | 2.9389 | 1.0 | 1.0 |
| 2.8288 | 8.51 | 400 | 2.2535 | 1.0 | 0.8004 |
| 0.907 | 12.77 | 600 | 0.4558 | 0.4243 | 0.1095 |
| 0.4071 | 17.02 | 800 | 0.4013 | 0.3468 | 0.0913 |
| 0.3 | 21.28 | 1000 | 0.4167 | 0.3075 | 0.0816 |
| 0.2544 | 25.53 | 1200 | 0.4132 | 0.2835 | 0.0762 |
| 0.2145 | 29.79 | 1400 | 0.3878 | 0.2693 | 0.0729 |
| 0.1923 | 34.04 | 1600 | 0.4023 | 0.2623 | 0.0702 |
| 0.1681 | 38.3 | 1800 | 0.3984 | 0.2581 | 0.0686 |
| 0.1598 | 42.55 | 2000 | 0.3982 | 0.2493 | 0.0663 |
| 0.1464 | 46.81 | 2200 | 0.4087 | 0.2461 | 0.0666 |
### Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0
|