readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: wav2vec2-xls-r-300m-th-v2
    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. -->
  
  # wav2vec2-xls-r-300m-th-v2
  
  This model is a fine-tuned version of [Botnoi/wav2vec2-xls-r-300m-th-v1](https://huggingface.co/Botnoi/wav2vec2-xls-r-300m-th-v1) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3630
  - Wer: 0.3962
  - Cer: 0.0942
  - Clean Cer: 0.0767
  
  ## 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: 4.533e-08
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - training_steps: 9000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    | Clean Cer |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:---------:|
  | 0.3323        | 0.68  | 1000 | 0.3635          | 0.3961 | 0.0942 | 0.0767    |
  | 0.3386        | 1.36  | 2000 | 0.3632          | 0.3962 | 0.0943 | 0.0768    |
  | 0.3453        | 2.03  | 3000 | 0.3632          | 0.3964 | 0.0943 | 0.0768    |
  | 0.3392        | 2.71  | 4000 | 0.3632          | 0.3961 | 0.0943 | 0.0767    |
  | 0.3399        | 3.39  | 5000 | 0.3634          | 0.3961 | 0.0942 | 0.0768    |
  | 0.347         | 4.07  | 6000 | 0.3632          | 0.3961 | 0.0942 | 0.0767    |
  | 0.3414        | 4.74  | 7000 | 0.3631          | 0.3962 | 0.0942 | 0.0767    |
  | 0.3378        | 5.42  | 8000 | 0.3631          | 0.3961 | 0.0942 | 0.0767    |
  | 0.3421        | 6.1   | 9000 | 0.3630          | 0.3962 | 0.0942 | 0.0767    |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  