readme: ---
  language:
  - sl
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_8_0
  - generated_from_trainer
  - sl
  - robust-speech-event
  - model_for_talk
  - hf-asr-leaderboard
  datasets:
  - mozilla-foundation/common_voice_8_0
  model-index:
  - name: wav2vec2-xls-r-sl-a2
    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: 0.21695212999560826
      - name: Test CER
        type: cer
        value: 0.052850080572474256
    - 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: 0.560722380639029
      - name: Test CER
        type: cer
        value: 0.2279626093074681
    - 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: 56.07
    - 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: 56.19
  ---
  
  <!-- 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: 0.2855
  - Wer: 0.2401
  
  ##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-a2 --dataset mozilla-foundation/common_voice_8_0 --config sl --split test --log_outputs
  
  2. To evaluate on speech-recognition-community-v2/dev_data
  
  Votic language not found 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: 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 6.9294        | 6.1   | 500  | 2.9712          | 1.0    |
  | 2.8305        | 12.2  | 1000 | 1.7073          | 0.9479 |
  | 1.4795        | 18.29 | 1500 | 0.5756          | 0.6397 |
  | 1.3433        | 24.39 | 2000 | 0.4968          | 0.5424 |
  | 1.1766        | 30.49 | 2500 | 0.4185          | 0.4743 |
  | 1.0017        | 36.59 | 3000 | 0.3303          | 0.3578 |
  | 0.9358        | 42.68 | 3500 | 0.3003          | 0.3051 |
  | 0.8358        | 48.78 | 4000 | 0.3045          | 0.2884 |
  | 0.7647        | 54.88 | 4500 | 0.2866          | 0.2677 |
  | 0.7482        | 60.98 | 5000 | 0.2829          | 0.2585 |
  | 0.6943        | 67.07 | 5500 | 0.2782          | 0.2478 |
  | 0.6586        | 73.17 | 6000 | 0.2911          | 0.2537 |
  | 0.6425        | 79.27 | 6500 | 0.2817          | 0.2462 |
  | 0.6067        | 85.37 | 7000 | 0.2910          | 0.2436 |
  | 0.5974        | 91.46 | 7500 | 0.2875          | 0.2430 |
  | 0.5812        | 97.56 | 8000 | 0.2852          | 0.2396 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.2.dev0
  - Tokenizers 0.11.0
  