readme: ---
  language:
  - rm-sursilv
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - hf-asr-leaderboard
  - robust-speech-event
  datasets:
  - mozilla-foundation/common_voice_8_0
  metrics:
  - wer
  model-index:
  - name: wav2vec2-xls-r-300m-rm-sursilv-d11
    results:
    - task:
        type: automatic-speech-recognition
        name: Speech Recognition
      dataset:
        type: mozilla-foundation/common_voice_8_0
        name: Common Voice 8
        args: rm-sursilv
      metrics:
      - type: wer
        value: 0.24094169578811844
        name: Test WER
      - name: Test CER
        type: cer
        value: 0.049832791672554284
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: rm-sursilv
      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 - RM-SURSILV dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2511
  - Wer: 0.2415 
  
  #### Evaluation Commands
  
  1. To evaluate on mozilla-foundation/common_voice_8_0 with test split
  
  python eval.py --model_id DrishtiSharma/wav2vec2-xls-r-300m-rm-sursilv-d11 --dataset mozilla-foundation/common_voice_8_0 --config rm-sursilv --split test --log_outputs
  
  2. To evaluate on speech-recognition-community-v2/dev_data
  
  Romansh-Sursilv language isn't available in speech-recognition-community-v2/dev_data
  
  
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 7e-05
  - train_batch_size: 32
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 2000
  - num_epochs: 125.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch  | Step  | Validation Loss | Wer    |
  |:-------------:|:------:|:-----:|:---------------:|:------:|
  | 2.3958        | 17.44  | 1500  | 0.6808          | 0.6521 |
  | 0.9663        | 34.88  | 3000  | 0.3023          | 0.3718 |
  | 0.7963        | 52.33  | 4500  | 0.2588          | 0.3046 |
  | 0.6893        | 69.77  | 6000  | 0.2436          | 0.2718 |
  | 0.6148        | 87.21  | 7500  | 0.2521          | 0.2572 |
  | 0.5556        | 104.65 | 9000  | 0.2490          | 0.2442 |
  | 0.5258        | 122.09 | 10500 | 0.2515          | 0.2442 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.2.dev0
  - Tokenizers 0.11.0
  