readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec-malayalam-checkpoint
    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. -->
  
  # wav2vec-malayalam-checkpoint
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6457
  - Wer: 0.6608
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 16
  - total_train_batch_size: 128
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 40
  - num_epochs: 150
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.6371        | 10.0  | 100  | 3.5200          | 1.0    |
  | 3.3014        | 20.0  | 200  | 3.2092          | 1.0    |
  | 1.2997        | 30.0  | 300  | 0.7134          | 0.8847 |
  | 0.5078        | 40.0  | 400  | 0.5805          | 0.7841 |
  | 0.3795        | 50.0  | 500  | 0.5604          | 0.7289 |
  | 0.2809        | 60.0  | 600  | 0.5962          | 0.7055 |
  | 0.2381        | 70.0  | 700  | 0.6099          | 0.6938 |
  | 0.2046        | 80.0  | 800  | 0.6237          | 0.6862 |
  | 0.1826        | 90.0  | 900  | 0.6204          | 0.6755 |
  | 0.1627        | 100.0 | 1000 | 0.6335          | 0.6751 |
  | 0.1453        | 110.0 | 1100 | 0.6446          | 0.6739 |
  | 0.1359        | 120.0 | 1200 | 0.6277          | 0.6648 |
  | 0.1274        | 130.0 | 1300 | 0.6356          | 0.6573 |
  | 0.1189        | 140.0 | 1400 | 0.6417          | 0.6601 |
  | 0.1146        | 150.0 | 1500 | 0.6457          | 0.6608 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.9.0+cu111
  - Datasets 1.18.3
  - Tokenizers 0.10.3
  