readme: ---
  language:
  - kk
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_8_0
  - generated_from_trainer
  - kk
  - robust-speech-event
  - model_for_talk
  - hf-asr-leaderboard
  datasets:
  - mozilla-foundation/common_voice_8_0
  model-index:
  - name: wav2vec2-xls-r-300m-kk-n2
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 8
        type: mozilla-foundation/common_voice_8_0
        args: tt
      metrics:
      - name: Test WER
        type: wer
        value: 0.4355
      - name: Test CER
        type: cer
        value: 0.10469915859660263
    - 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: 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 - KK dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7149
  - Wer: 0.451
  
  ### 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-kk-n2 --dataset mozilla-foundation/common_voice_8_0 --config kk --split test --log_outputs
  
  2. To evaluate on speech-recognition-community-v2/dev_data
  
  Kazakh language not found in speech-recognition-community-v2/dev_data!
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 0.000222
  - 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: 1000
  - num_epochs: 150.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch  | Step | Validation Loss | Wer    |
  |:-------------:|:------:|:----:|:---------------:|:------:|
  | 9.6799        | 9.09   | 200  | 3.6119          | 1.0    |
  | 3.1332        | 18.18  | 400  | 2.5352          | 1.005  |
  | 1.0465        | 27.27  | 600  | 0.6169          | 0.682  |
  | 0.3452        | 36.36  | 800  | 0.6572          | 0.607  |
  | 0.2575        | 45.44  | 1000 | 0.6527          | 0.578  |
  | 0.2088        | 54.53  | 1200 | 0.6828          | 0.551  |
  | 0.158         | 63.62  | 1400 | 0.7074          | 0.5575 |
  | 0.1309        | 72.71  | 1600 | 0.6523          | 0.5595 |
  | 0.1074        | 81.8   | 1800 | 0.7262          | 0.5415 |
  | 0.087         | 90.89  | 2000 | 0.7199          | 0.521  |
  | 0.0711        | 99.98  | 2200 | 0.7113          | 0.523  |
  | 0.0601        | 109.09 | 2400 | 0.6863          | 0.496  |
  | 0.0451        | 118.18 | 2600 | 0.6998          | 0.483  |
  | 0.0378        | 127.27 | 2800 | 0.6971          | 0.4615 |
  | 0.0319        | 136.36 | 3000 | 0.7119          | 0.4475 |
  | 0.0305        | 145.44 | 3200 | 0.7181          | 0.459  |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.2.dev0
  - Tokenizers 0.11.0
  