readme: ---
  language:
  - kmr
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - generated_from_trainer
  - hf-asr-leaderboard
  - kmr
  - model_for_talk
  - mozilla-foundation/common_voice_7_0
  - robust-speech-event
  datasets:
  - mozilla-foundation/common_voice_7_0
  model-index:
  - name: XLS-R-300M - Kurmanji Kurdish
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 7
        type: mozilla-foundation/common_voice_7_0
        args: kmr
      metrics:
      - name: Test WER
        type: wer
        value: 102.308
      - name: Test CER
        type: cer
        value: 538.748
  ---
  
  <!-- 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. -->
  
  # wav2vec2-large-xls-r-300m-kurdish
  
  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_7_0 - KMR dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2548
  - Wer: 0.2688
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  More information needed
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 7e-05
  - train_batch_size: 32
  - eval_batch_size: 1
  - 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: 100.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 1.3161        | 12.27 | 2000  | 0.4199          | 0.4797 |
  | 1.0643        | 24.54 | 4000  | 0.2982          | 0.3721 |
  | 0.9718        | 36.81 | 6000  | 0.2762          | 0.3333 |
  | 0.8772        | 49.08 | 8000  | 0.2586          | 0.3051 |
  | 0.8236        | 61.35 | 10000 | 0.2575          | 0.2865 |
  | 0.7745        | 73.62 | 12000 | 0.2603          | 0.2816 |
  | 0.7297        | 85.89 | 14000 | 0.2539          | 0.2727 |
  | 0.7079        | 98.16 | 16000 | 0.2554          | 0.2681 |
  
  
  ### Framework versions
  
  - Transformers 4.16.0.dev0
  - Pytorch 1.10.1+cu102
  - Datasets 1.17.1.dev0
  - Tokenizers 0.11.0
  