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Change WER to percentage
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
language:
  - ga
model-index:
  - name: wav2vec2-large-xls-r-300m-irish-colab
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_11_0
          type: mozilla-foundation/common_voice_11_0
          config: ga-IE
          split: train+validation
          args: ga-IE
        metrics:
          - name: Wer
            type: wer
            value: 52.44117647058824

wav2vec2-large-xls-r-300m-irish-colab

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: 1.148
  • Wer: 52.4

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: 0.0003
  • 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: 500
  • num_epochs: 30
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
4.6516 12.12 400 1.2867 0.7653
0.4188 24.24 800 1.1262 0.5509

Framework versions

  • Transformers 4.25.1
  • Pytorch 1.10.0+cu113
  • Datasets 2.0.0
  • Tokenizers 0.13.2