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End of training
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metadata
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
  - generated_from_trainer
datasets:
  - xtreme_s
metrics:
  - wer
model-index:
  - name: wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod7
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: xtreme_s
          type: xtreme_s
          config: fleurs.id_id
          split: test
          args: fleurs.id_id
        metrics:
          - name: Wer
            type: wer
            value: 0.5032929202215237

wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod7

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

  • Loss: 1.0673
  • Wer: 0.5033

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: 0.001
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 600
  • num_epochs: 90
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
5.2829 7.79 300 2.8538 1.0
1.9733 15.58 600 0.8923 0.7851
0.4186 23.38 900 0.8297 0.6443
0.2077 31.17 1200 0.8573 0.6011
0.1535 38.96 1500 0.9490 0.5800
0.1163 46.75 1800 1.0380 0.5652
0.1001 54.55 2100 0.9354 0.5417
0.0845 62.34 2400 1.0226 0.5364
0.0711 70.13 2700 1.0799 0.5220
0.0588 77.92 3000 1.0550 0.5050
0.0492 85.71 3300 1.0673 0.5033

Framework versions

  • Transformers 4.39.0
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2