readme: ---
  language:
  - sl
  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
  - sl
  datasets:
  - mozilla-foundation/common_voice_8_0
  model-index:
  - name: wav2vec2-xls-r-sl-a1
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 8
        type: mozilla-foundation/common_voice_8_0
        args: sl
      metrics:
      - name: Test WER
        type: wer
        value: 0.20626555409164105
      - name: Test CER
        type: cer
        value: 0.051648321634392154
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: sl
      metrics:
      - name: Test WER
        type: wer
        value: 0.5406156320830592
      - name: Test CER
        type: cer
        value: 0.22249723590310583
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Test Data
        type: speech-recognition-community-v2/eval_data
        args: sl
      metrics:
      - name: Test WER
        type: wer
        value: 55.24
  ---
  
  <!-- 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 - SL dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2756
  - Wer: 0.2279
  
  ### Evaluation Commands
  1. To evaluate on mozilla-foundation/common_voice_8_0 with test split
  
  python eval.py --model_id DrishtiSharma/wav2vec2-xls-r-sl-a1 --dataset mozilla-foundation/common_voice_8_0 --config sl --split test --log_outputs
  
  2. To evaluate on speech-recognition-community-v2/dev_data
  
  python eval.py --model_id DrishtiSharma/wav2vec2-xls-r-sl-a1 --dataset speech-recognition-community-v2/dev_data --config sl --split validation --chunk_length_s 10 --stride_length_s 1
  
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 7.1e-05
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 1000
  - num_epochs: 100.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.3881        | 6.1   | 500  | 2.9710          | 1.0    |
  | 2.6401        | 12.2  | 1000 | 1.7677          | 0.9734 |
  | 1.5152        | 18.29 | 1500 | 0.5564          | 0.6011 |
  | 1.2191        | 24.39 | 2000 | 0.4319          | 0.4390 |
  | 1.0237        | 30.49 | 2500 | 0.3141          | 0.3175 |
  | 0.8892        | 36.59 | 3000 | 0.2748          | 0.2689 |
  | 0.8296        | 42.68 | 3500 | 0.2680          | 0.2534 |
  | 0.7602        | 48.78 | 4000 | 0.2820          | 0.2506 |
  | 0.7186        | 54.88 | 4500 | 0.2672          | 0.2398 |
  | 0.6887        | 60.98 | 5000 | 0.2729          | 0.2402 |
  | 0.6507        | 67.07 | 5500 | 0.2767          | 0.2361 |
  | 0.6226        | 73.17 | 6000 | 0.2817          | 0.2332 |
  | 0.6024        | 79.27 | 6500 | 0.2679          | 0.2279 |
  | 0.5787        | 85.37 | 7000 | 0.2837          | 0.2316 |
  | 0.5744        | 91.46 | 7500 | 0.2838          | 0.2284 |
  | 0.5556        | 97.56 | 8000 | 0.2763          | 0.2281 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.2.dev0
  - Tokenizers 0.11.0
  