readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - uob_singlish
  model-index:
  - name: Malaya-speech_fine-tune_realcase_30_Jun_lm
    results: []
  ---
  
  <!-- 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. -->
  
  # Malaya-speech_fine-tune_realcase_30_Jun_lm
  
  This model is a fine-tuned version of [malay-huggingface/wav2vec2-xls-r-300m-mixed](https://huggingface.co/malay-huggingface/wav2vec2-xls-r-300m-mixed) on the uob_singlish dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7669
  - Wer: 0.3194
  
  ## 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: 0.0002
  - train_batch_size: 2
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 4
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 1.2487        | 1.82  | 20   | 0.7188          | 0.3403 |
  | 0.6386        | 3.64  | 40   | 0.7061          | 0.3264 |
  | 0.3525        | 5.45  | 60   | 0.7403          | 0.3542 |
  | 0.3088        | 7.27  | 80   | 0.7483          | 0.2986 |
  | 0.2609        | 9.09  | 100  | 0.7669          | 0.3194 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.10.3
  