readme: ---
  tags:
  - generated_from_keras_callback
  model-index:
  - name: wav2vec2-xls-r-300m-mixed
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information Keras had access to. You should
  probably proofread and complete it, then remove this comment. -->
  
  # wav2vec2-xls-r-300m-mixed
  
  Finetuned https://huggingface.co/facebook/wav2vec2-xls-r-300m on https://github.com/huseinzol05/malaya-speech/tree/master/data/mixed-stt
  
  This model was finetuned on 3 languages,
  
  1. Malay
  2. Singlish
  3. Mandarin
  
  **This model trained on a single RTX 3090 Ti 24GB VRAM, provided by https://mesolitica.com/**. 
  
  ## Evaluation set
  
  Evaluation set from https://github.com/huseinzol05/malaya-speech/tree/master/pretrained-model/prepare-stt with sizes,
  
  ```
  len(malay), len(singlish), len(mandarin)
  -> (765, 3579, 614)
  ```
  
  It achieves the following results on the evaluation set based on [evaluate-gpu.ipynb](evaluate-gpu.ipynb):
  
  Mixed evaluation,
  
  ```
  CER: 0.0481054244857041
  WER: 0.1322198446007387
  CER with LM: 0.041196586938584696
  WER with LM: 0.09880169127621556
  ```
  
  Malay evaluation,
  
  ```
  CER: 0.051636391937588406
  WER: 0.19561999547293663
  CER with LM: 0.03917689630621449
  WER with LM: 0.12710746406824835
  ```
  
  Singlish evaluation,
  
  ```
  CER: 0.0494915200071987
  WER: 0.12763802881676573
  CER with LM: 0.04271234986432335
  WER with LM: 0.09677160640413336
  ```
  
  Mandarin evaluation,
  
  ```
  CER: 0.035626554824269824
  WER: 0.07993515937860181
  CER with LM: 0.03487760945087219
  WER with LM: 0.07536807168546154
  ```
  
  Language model from https://huggingface.co/huseinzol05/language-model-bahasa-manglish-combined