readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - uob_singlish
  model-index:
  - name: Malaya-speech_fine-tune_realcase_27_Jun
    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_27_Jun
  
  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: 0.9159
  - Wer: 0.3819
  
  ## 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 1.3176        | 1.82  | 20   | 0.8928          | 0.3542 |
  | 0.6716        | 3.64  | 40   | 0.9123          | 0.3681 |
  | 0.3484        | 5.45  | 60   | 0.9509          | 0.3681 |
  | 0.3064        | 7.27  | 80   | 0.9227          | 0.3958 |
  | 0.3017        | 9.09  | 100  | 0.9159          | 0.3819 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.10.3
  