readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-large-xlsr-tamil-commonvoice
    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-large-xlsr-tamil-commonvoice
  
  This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6145
  - Wer: 0.8512
  
  ## 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: 0.0003
  - train_batch_size: 16
  - eval_batch_size: 8
  - 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
  - lr_scheduler_warmup_steps: 200
  - num_epochs: 20
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 12.0478       | 1.05  | 100  | 3.3867          | 1.0    |
  | 3.2522        | 2.11  | 200  | 3.2770          | 1.0    |
  | 3.1689        | 3.16  | 300  | 3.1135          | 1.0039 |
  | 2.9278        | 4.21  | 400  | 2.0485          | 1.3109 |
  | 1.3592        | 5.26  | 500  | 0.8044          | 1.0988 |
  | 0.7472        | 6.32  | 600  | 0.6571          | 0.9474 |
  | 0.5842        | 7.37  | 700  | 0.6079          | 0.9477 |
  | 0.4831        | 8.42  | 800  | 0.6083          | 0.9491 |
  | 0.4259        | 9.47  | 900  | 0.5916          | 0.8973 |
  | 0.3817        | 10.53 | 1000 | 0.6070          | 0.9147 |
  | 0.338         | 11.58 | 1100 | 0.5873          | 0.8617 |
  | 0.3123        | 12.63 | 1200 | 0.5983          | 0.8844 |
  | 0.287         | 13.68 | 1300 | 0.6146          | 0.8988 |
  | 0.2706        | 14.74 | 1400 | 0.6068          | 0.8754 |
  | 0.2505        | 15.79 | 1500 | 0.5996          | 0.8638 |
  | 0.2412        | 16.84 | 1600 | 0.6106          | 0.8481 |
  | 0.2176        | 17.89 | 1700 | 0.6152          | 0.8520 |
  | 0.2255        | 18.95 | 1800 | 0.6150          | 0.8540 |
  | 0.216         | 20.0  | 1900 | 0.6145          | 0.8512 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu102
  - Datasets 1.13.3
  - Tokenizers 0.10.3
  