readme: ---
  language:
  - hi
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_7_0
  - generated_from_trainer
  - hi
  - robust-speech-event
  - hf-asr-leaderboard
  datasets:
  - mozilla-foundation/common_voice_7_0
  model-index:
  - name: wav2vec2-large-xls-r-300m-hi-CV7
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 7
        type: mozilla-foundation/common_voice_7_0
        args: hi
      metrics:
      - name: Test WER
        type: wer
        value: 35.31946325249292
      - name: Test CER
        type: cer
        value: 11.310803379493076
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: vot
      metrics:
      - name: Test WER
        type: wer
        value: NA
      - name: Test CER
        type: cer
        value: NA
  ---
  
  <!-- 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-hi-CV7
  
  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_7_0 - HI dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6588
  - Wer: 0.2987
  
  ### 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-hi-CV7 --dataset mozilla-foundation/common_voice_7_0 --config hi --split test --log_outputs
  
  2. To evaluate on speech-recognition-community-v2/dev_data
  
  NA
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  #
  - 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: 2000
  - num_epochs: 60
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 12.809        | 1.36  | 200  | 6.2066          | 1.0    |
  | 4.3402        | 2.72  | 400  | 3.5184          | 1.0    |
  | 3.4365        | 4.08  | 600  | 3.2779          | 1.0    |
  | 1.8643        | 5.44  | 800  | 0.9875          | 0.6270 |
  | 0.7504        | 6.8   | 1000 | 0.6382          | 0.4666 |
  | 0.5328        | 8.16  | 1200 | 0.6075          | 0.4505 |
  | 0.4364        | 9.52  | 1400 | 0.5785          | 0.4215 |
  | 0.3777        | 10.88 | 1600 | 0.6279          | 0.4227 |
  | 0.3374        | 12.24 | 1800 | 0.6536          | 0.4192 |
  | 0.3236        | 13.6  | 2000 | 0.5911          | 0.4047 |
  | 0.2877        | 14.96 | 2200 | 0.5955          | 0.4097 |
  | 0.2643        | 16.33 | 2400 | 0.5923          | 0.3744 |
  | 0.2421        | 17.68 | 2600 | 0.6307          | 0.3814 |
  | 0.2218        | 19.05 | 2800 | 0.6036          | 0.3764 |
  | 0.2046        | 20.41 | 3000 | 0.6286          | 0.3797 |
  | 0.191         | 21.77 | 3200 | 0.6517          | 0.3889 |
  | 0.1856        | 23.13 | 3400 | 0.6193          | 0.3661 |
  | 0.1721        | 24.49 | 3600 | 0.7034          | 0.3727 |
  | 0.1656        | 25.85 | 3800 | 0.6293          | 0.3591 |
  | 0.1532        | 27.21 | 4000 | 0.6075          | 0.3611 |
  | 0.1507        | 28.57 | 4200 | 0.6313          | 0.3565 |
  | 0.1381        | 29.93 | 4400 | 0.6564          | 0.3578 |
  | 0.1359        | 31.29 | 4600 | 0.6724          | 0.3543 |
  | 0.1248        | 32.65 | 4800 | 0.6789          | 0.3512 |
  | 0.1198        | 34.01 | 5000 | 0.6442          | 0.3539 |
  | 0.1125        | 35.37 | 5200 | 0.6676          | 0.3419 |
  | 0.1036        | 36.73 | 5400 | 0.7017          | 0.3435 |
  | 0.0982        | 38.09 | 5600 | 0.6828          | 0.3319 |
  | 0.0971        | 39.45 | 5800 | 0.6112          | 0.3351 |
  | 0.0968        | 40.81 | 6000 | 0.6424          | 0.3252 |
  | 0.0893        | 42.18 | 6200 | 0.6707          | 0.3304 |
  | 0.0878        | 43.54 | 6400 | 0.6432          | 0.3236 |
  | 0.0827        | 44.89 | 6600 | 0.6696          | 0.3240 |
  | 0.0788        | 46.26 | 6800 | 0.6564          | 0.3180 |
  | 0.0753        | 47.62 | 7000 | 0.6574          | 0.3130 |
  | 0.0674        | 48.98 | 7200 | 0.6698          | 0.3175 |
  | 0.0676        | 50.34 | 7400 | 0.6441          | 0.3142 |
  | 0.0626        | 51.7  | 7600 | 0.6642          | 0.3121 |
  | 0.0617        | 53.06 | 7800 | 0.6615          | 0.3117 |
  | 0.0599        | 54.42 | 8000 | 0.6634          | 0.3059 |
  | 0.0538        | 55.78 | 8200 | 0.6464          | 0.3033 |
  | 0.0571        | 57.14 | 8400 | 0.6503          | 0.3018 |
  | 0.0491        | 58.5  | 8600 | 0.6625          | 0.3025 |
  | 0.0511        | 59.86 | 8800 | 0.6588          | 0.2987 |
  
  
  ### Framework versions
  
  - Transformer