readme: ---
  language:
  - bn
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_9_0
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_9_0
  metrics:
  - wer
  model-index:
  - name: XLS-R-300M - Bengali
    results:
    - task:
        type: automatic-speech-recognition
        name: Speech Recognition
      dataset:
        type: mozilla-foundation/common_voice_9_0
        name: Common Voice 9
        args: bn
      metrics:
      - type: wer
        value: 20.150
        name: Test WER
      - name: Test CER
        type: cer
        value: 4.813
  ---
  
  <!-- 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. -->
  
  # 
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_9_0 - BN dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2297
  - Wer: 0.2850
  - Cer: 0.0660
  
  ## 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: 7.5e-05
  - train_batch_size: 64
  - eval_batch_size: 64
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 128
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_ratio: 0.1
  - training_steps: 8692
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
  | 3.675         | 2.3   | 400  | 3.5052          | 1.0    | 1.0    |
  | 3.0446        | 4.6   | 800  | 2.2759          | 1.0052 | 0.5215 |
  | 1.7276        | 6.9   | 1200 | 0.7083          | 0.6697 | 0.1969 |
  | 1.5171        | 9.2   | 1600 | 0.5328          | 0.5733 | 0.1568 |
  | 1.4176        | 11.49 | 2000 | 0.4571          | 0.5161 | 0.1381 |
  | 1.343         | 13.79 | 2400 | 0.3910          | 0.4522 | 0.1160 |
  | 1.2743        | 16.09 | 2800 | 0.3534          | 0.4137 | 0.1044 |
  | 1.2396        | 18.39 | 3200 | 0.3278          | 0.3877 | 0.0959 |
  | 1.2035        | 20.69 | 3600 | 0.3109          | 0.3741 | 0.0917 |
  | 1.1745        | 22.99 | 4000 | 0.2972          | 0.3618 | 0.0882 |
  | 1.1541        | 25.29 | 4400 | 0.2836          | 0.3427 | 0.0832 |
  | 1.1372        | 27.59 | 4800 | 0.2759          | 0.3357 | 0.0812 |
  | 1.1048        | 29.89 | 5200 | 0.2669          | 0.3284 | 0.0783 |
  | 1.0966        | 32.18 | 5600 | 0.2678          | 0.3249 | 0.0775 |
  | 1.0747        | 34.48 | 6000 | 0.2547          | 0.3134 | 0.0748 |
  | 1.0593        | 36.78 | 6400 | 0.2491          | 0.3077 | 0.0728 |
  | 1.0417        | 39.08 | 6800 | 0.2450          | 0.3012 | 0.0711 |
  | 1.024         | 41.38 | 7200 | 0.2402          | 0.2956 | 0.0694 |
  | 1.0106        | 43.68 | 7600 | 0.2351          | 0.2915 | 0.0681 |
  | 1.0014        | 45.98 | 8000 | 0.2328          | 0.2896 | 0.0673 |
  | 0.9999        | 48.28 | 8400 | 0.2318          | 0.2866 | 0.0667 |
  
  
  ### Framework versions
  
  - Transformers 4.19.0.dev0
  - Pytorch 1.11.0+cu102
  - Datasets 2.1.1.dev0
  - Tokenizers 0.12.1
  