readme: ---
  language:
  - bg
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - bg
  - generated_from_trainer
  - hf-asr-leaderboard
  - model_for_talk
  - mozilla-foundation/common_voice_8_0
  - robust-speech-event
  datasets:
  - mozilla-foundation/common_voice_8_0
  model-index:
  - name: wav2vec2-large-xls-r-300m-bg-v1
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 8
        type: mozilla-foundation/common_voice_8_0
        args: bg
      metrics:
      - name: Test WER
        type: wer
        value: 0.4709579127785184
      - name: Test CER
        type: cer
        value: 0.10205125354383235
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: bg
      metrics:
      - name: Test WER
        type: wer
        value: 0.7053128872366791
      - name: Test CER
        type: cer
        value: 0.210804311998487
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Test Data
        type: speech-recognition-community-v2/eval_data
        args: bg
      metrics:
      - name: Test WER
        type: wer
        value: 72.6
  ---
  
  <!-- 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 - BG dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5197
  - Wer: 0.4689
  
  ### 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-bg-v1 --dataset mozilla-foundation/common_voice_8_0 --config bg --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-bg-v1 --dataset speech-recognition-community-v2/dev_data --config bg --split validation --chunk_length_s 10 --stride_length_s 1
  
  ### 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: 50.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 4.3711        | 2.61  | 300  | 4.3122          | 1.0    |
  | 3.1653        | 5.22  | 600  | 3.1156          | 1.0    |
  | 2.8904        | 7.83  | 900  | 2.8421          | 0.9918 |
  | 0.9207        | 10.43 | 1200 | 0.9895          | 0.8689 |
  | 0.6384        | 13.04 | 1500 | 0.6994          | 0.7700 |
  | 0.5215        | 15.65 | 1800 | 0.5628          | 0.6443 |
  | 0.4573        | 18.26 | 2100 | 0.5316          | 0.6174 |
  | 0.3875        | 20.87 | 2400 | 0.4932          | 0.5779 |
  | 0.3562        | 23.48 | 2700 | 0.4972          | 0.5475 |
  | 0.3218        | 26.09 | 3000 | 0.4895          | 0.5219 |
  | 0.2954        | 28.7  | 3300 | 0.5226          | 0.5192 |
  | 0.287         | 31.3  | 3600 | 0.4957          | 0.5146 |
  | 0.2587        | 33.91 | 3900 | 0.4944          | 0.4893 |
  | 0.2496        | 36.52 | 4200 | 0.4976          | 0.4895 |
  | 0.2365        | 39.13 | 4500 | 0.5185          | 0.4819 |
  | 0.2264        | 41.74 | 4800 | 0.5152          | 0.4776 |
  | 0.2224        | 44.35 | 5100 | 0.5031          | 0.4746 |
  | 0.2096        | 46.96 | 5400 | 0.5062          | 0.4708 |
  | 0.2038        | 49.57 | 5700 | 0.5217          | 0.4698 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.2.dev0
  - Tokenizers 0.11.0
  