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metadata
license: apache-2.0
language: tr
tags:
  - generated_from_trainer
  - robust-speech-event
datasets:
  - common_voice
model-index:
  - name: wav2vec2-xls-r-300m-Tr-med-CommonVoice8
    results:
      - task:
          name: Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice tr
          type: common_voice
          args: tr
        metrics:
          - name: Test WER
            type: wer
            value: 49.14

wav2vec2-xls-r-300m-Tr-med-CommonVoice8

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2556
  • Wer: 0.4914

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: 0.0001
  • 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: 300
  • num_epochs: 20
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
1.4876 6.66 5000 0.3252 0.5784
0.6919 13.32 10000 0.2720 0.5172
0.5919 19.97 15000 0.2556 0.4914

Framework versions

  • Transformers 4.11.3
  • Pytorch 1.10.0+cu111
  • Datasets 1.18.1
  • Tokenizers 0.10.3