readme: ---
  language:
  - pa-IN
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_8_0
  - generated_from_trainer
  - pa-IN
  - robust-speech-event
  - hf-asr-leaderboard
  datasets:
  - mozilla-foundation/common_voice_8_0
  model-index:
  - name: wav2vec2-large-xls-r-300m-pa-IN-dx1
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 8
        type: mozilla-foundation/common_voice_8_0
        args: pa-IN
      metrics:
      - name: Test WER
        type: wer
        value: 0.48725989807918463
      - name: Test CER
        type: cer
        value: 0.1687305197540224
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: pa-IN
      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. -->
  
  # 
  
  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 - PA-IN dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.0855
  - Wer: 0.4755
  
  
  ### 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-pa-IN-dx1 --dataset mozilla-foundation/common_voice_8_0 --config pa-IN --split test --log_outputs
  
  2. To evaluate on speech-recognition-community-v2/dev_data
  
  Punjabi language isn't available in speech-recognition-community-v2/dev_data
  
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 0.0003
  - train_batch_size: 16
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 1200
  - num_epochs: 100.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.4607        | 9.26  | 500  | 2.7746          | 1.0416 |
  | 0.3442        | 18.52 | 1000 | 0.9114          | 0.5911 |
  | 0.2213        | 27.78 | 1500 | 0.9687          | 0.5751 |
  | 0.1242        | 37.04 | 2000 | 1.0204          | 0.5461 |
  | 0.0998        | 46.3  | 2500 | 1.0250          | 0.5233 |
  | 0.0727        | 55.56 | 3000 | 1.1072          | 0.5382 |
  | 0.0605        | 64.81 | 3500 | 1.0588          | 0.5073 |
  | 0.0458        | 74.07 | 4000 | 1.0818          | 0.5069 |
  | 0.0338        | 83.33 | 4500 | 1.0948          | 0.5108 |
  | 0.0223        | 92.59 | 5000 | 1.0986          | 0.4775 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.2.dev0
  - Tokenizers 0.11.0
  