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metadata
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

wav2vec2-large-xls-r-300m-kurdish

This model is a fine-tuned version of 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