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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - common_voice
metrics:
  - wer
model-index:
  - name: wav2vec2-common_voice-tr-demo
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice
          type: common_voice
          config: tr
          split: test
          args: tr
        metrics:
          - name: Wer
            type: wer
            value: 0.49443366356858337

wav2vec2-common_voice-tr-demo

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the common_voice dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5314
  • Wer: 0.4944

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: 0.0002
  • train_batch_size: 32
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 20.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
No log 1.83 100 4.1084 1.0
No log 3.67 200 3.1519 1.0
No log 5.5 300 1.9348 0.9799
No log 7.34 400 0.7185 0.7490
3.6165 9.17 500 0.6041 0.6368
3.6165 11.01 600 0.5610 0.5771
3.6165 12.84 700 0.5292 0.5398
3.6165 14.68 800 0.5242 0.5083
3.6165 16.51 900 0.5443 0.5037
0.1894 18.35 1000 0.5314 0.4944

Framework versions

  • Transformers 4.29.2
  • Pytorch 2.0.1
  • Datasets 2.13.1
  • Tokenizers 0.13.2