readme: ---
  language:
  - or
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_8_0
  - generated_from_trainer
  - or
  - robust-speech-event
  - model_for_talk
  - hf-asr-leaderboard
  datasets:
  - mozilla-foundation/common_voice_8_0
  model-index:
  - name: wav2vec2-large-xls-r-300m-or-d5
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 8
        type: mozilla-foundation/common_voice_8_0
        args: or
      metrics:
      - name: Test WER
        type: wer
        value: 0.579136690647482
      - name: Test CER
        type: cer
        value: 0.1572148018392818
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: or
      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-or-d5
  
  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 - OR dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.9571
  - Wer: 0.5450
  
  ### 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-or-d5 --dataset mozilla-foundation/common_voice_8_0 --config or --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-or-d5 --dataset speech-recognition-community-v2/dev_data --config or --split validation --chunk_length_s 10 --stride_length_s 1
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 0.000111
  - 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 9.2958        | 12.5  | 300  | 4.9014          | 1.0    |
  | 3.4065        | 25.0  | 600  | 3.5150          | 1.0    |
  | 1.5402        | 37.5  | 900  | 0.8356          | 0.7249 |
  | 0.6049        | 50.0  | 1200 | 0.7754          | 0.6349 |
  | 0.4074        | 62.5  | 1500 | 0.7994          | 0.6217 |
  | 0.3097        | 75.0  | 1800 | 0.8815          | 0.5985 |
  | 0.2593        | 87.5  | 2100 | 0.8532          | 0.5754 |
  | 0.2097        | 100.0 | 2400 | 0.9077          | 0.5648 |
  | 0.1784        | 112.5 | 2700 | 0.9047          | 0.5668 |
  | 0.1567        | 125.0 | 3000 | 0.9019          | 0.5728 |
  | 0.1315        | 137.5 | 3300 | 0.9295          | 0.5827 |
  | 0.1125        | 150.0 | 3600 | 0.9256          | 0.5681 |
  | 0.1035        | 162.5 | 3900 | 0.9148          | 0.5496 |
  | 0.0901        | 175.0 | 4200 | 0.9480          | 0.5483 |
  | 0.0817        | 187.5 | 4500 | 0.9799          | 0.5516 |
  | 0.079         | 200.0 | 4800 | 0.9571          | 0.5450 |
  
  
  ### Framework versions
  
  - Transformers 4.16.2
  - Pytorch 1.10.0+cu111
  - Datasets 1.18.3
  - Tokenizers 0.11.0
  
  
  
  