readme: ---
  license: cc-by-nc-4.0
  tags:
  - generated_from_trainer
  model-index:
  - name: v2-fine-tune-wav2vec2-Vietnamese-ARS-demo
    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. -->
  
  # v2-fine-tune-wav2vec2-Vietnamese-ARS-demo
  
  This model is a fine-tuned version of [nguyenvulebinh/wav2vec2-base-vietnamese-250h](https://huggingface.co/nguyenvulebinh/wav2vec2-base-vietnamese-250h) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2515
  - Wer: 0.2235
  
  ## 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: 0.0001
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 1000
  - num_epochs: 6
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 8.8651        | 0.34  | 500  | 3.6919          | 0.9999 |
  | 3.54          | 0.69  | 1000 | 3.3584          | 1.0    |
  | 2.9478        | 1.03  | 1500 | 2.2535          | 0.9885 |
  | 1.9147        | 1.37  | 2000 | 0.9977          | 0.7260 |
  | 1.1667        | 1.71  | 2500 | 0.5577          | 0.4746 |
  | 0.844         | 2.06  | 3000 | 0.4129          | 0.3581 |
  | 0.6968        | 2.4   | 3500 | 0.3566          | 0.3090 |
  | 0.6273        | 2.74  | 4000 | 0.3243          | 0.2813 |
  | 0.5434        | 3.09  | 4500 | 0.3076          | 0.2631 |
  | 0.5069        | 3.43  | 5000 | 0.2902          | 0.2539 |
  | 0.4842        | 3.77  | 5500 | 0.2752          | 0.2432 |
  | 0.4318        | 4.12  | 6000 | 0.2854          | 0.2384 |
  | 0.3951        | 4.46  | 6500 | 0.2674          | 0.2350 |
  | 0.3954        | 4.8   | 7000 | 0.2628          | 0.2322 |
  | 0.3763        | 5.14  | 7500 | 0.2609          | 0.2284 |
  | 0.3652        | 5.49  | 8000 | 0.2508          | 0.2249 |
  | 0.3703        | 5.83  | 8500 | 0.2515          | 0.2235 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.12.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.12.1
  