readme: ---
  language:
  - sr
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - generated_from_trainer
  - hf-asr-leaderboard
  - model_for_talk
  - mozilla-foundation/common_voice_8_0
  - robust-speech-event
  - sr
  datasets:
  - mozilla-foundation/common_voice_8_0
  model-index:
  - name: wav2vec2-large-xls-r-300m-sr-v4
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 8
        type: mozilla-foundation/common_voice_8_0
        args: sr
      metrics:
      - name: Test WER
        type: wer
        value: 0.303313
      - name: Test CER
        type: cer
        value: 0.1048951
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: sr
      metrics:
      - name: Test WER
        type: wer
        value: 0.9486784706184245
      - name: Test CER
        type: cer
        value: 0.8084369606584945
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Test Data
        type: speech-recognition-community-v2/eval_data
        args: sr
      metrics:
      - name: Test WER
        type: wer
        value: 94.53
  ---
  
  <!-- 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-xls-r-300m-sr-v4
  
  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_8_0 - SR dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5570
  - Wer: 0.3038
  
  ### Evaluation Commands
  
  1. To evaluate on mozilla-foundation/common_voice_8_0 with test split
  
  python eval.py --model_id DrishtiSharma/wav2vec2-large-xls-r-300m-sr-v4 --dataset mozilla-foundation/common_voice_8_0 --config sr --split test --log_outputs
  
  2. To evaluate on speech-recognition-community-v2/dev_data
  
  python eval.py --model_id DrishtiSharma/wav2vec2-large-xls-r-300m-sr-v4 --dataset speech-recognition-community-v2/dev_data --config sr --split validation --chunk_length_s 10 --stride_length_s 1
  
  ### 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: 800
  - num_epochs: 200
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 8.2934        | 7.5   | 300  | 2.9777          | 0.9995 |
  | 1.5049        | 15.0  | 600  | 0.5036          | 0.4806 |
  | 0.3263        | 22.5  | 900  | 0.5822          | 0.4055 |
  | 0.2008        | 30.0  | 1200 | 0.5609          | 0.4032 |
  | 0.1543        | 37.5  | 1500 | 0.5203          | 0.3710 |
  | 0.1158        | 45.0  | 1800 | 0.6458          | 0.3985 |
  | 0.0997        | 52.5  | 2100 | 0.6227          | 0.4013 |
  | 0.0834        | 60.0  | 2400 | 0.6048          | 0.3836 |
  | 0.0665        | 67.5  | 2700 | 0.6197          | 0.3686 |
  | 0.0602        | 75.0  | 3000 | 0.5418          | 0.3453 |
  | 0.0524        | 82.5  | 3300 | 0.5310          | 0.3486 |
  | 0.0445        | 90.0  | 3600 | 0.5599          | 0.3374 |
  | 0.0406        | 97.5  | 3900 | 0.5958          | 0.3327 |
  | 0.0358        | 105.0 | 4200 | 0.6017          | 0.3262 |
  | 0.0302        | 112.5 | 4500 | 0.5613          | 0.3248 |
  | 0.0285        | 120.0 | 4800 | 0.5659          | 0.3462 |
  | 0.0213        | 127.5 | 5100 | 0.5568          | 0.3206 |
  | 0.0215        | 135.0 | 5400 | 0.6524          | 0.3472 |
  | 0.0162        | 142.5 | 5700 | 0.6223          | 0.3458 |
  | 0.0137        | 150.0 | 6000 | 0.6625          | 0.3313 |
  | 0.0114        | 157.5 | 6300 | 0.5739          | 0.3336 |
  | 0.0101        | 165.0 | 6600 | 0.5906          | 0.3285 |
  | 0.008         | 172.5 | 6900 | 0.5982          | 0.3112 |
  | 0.0076        | 180.0 | 7200 | 0.5399          | 0.3094 |
  | 0.0071        | 187.5 | 7500 | 0.5387          | 0.2991 |
  | 0.0057        | 195.0 | 7800 | 0.5570          | 0.3038 |
  
  
  ### Framework versions
  
  - Transformers 4.16.2
  - Pytorch 1.10.0+cu111
  - Datasets 1.18.2
  - Tokenizers 0.11.0
  