TrainEsperanto / README.md
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metadata
base_model: cpierse/wav2vec2-large-xlsr-53-esperanto
datasets:
  - audiofolder
library_name: transformers
license: apache-2.0
metrics:
  - wer
tags:
  - generated_from_trainer
model-index:
  - name: TrainEsperanto
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: audiofolder
          type: audiofolder
          config: default
          split: None
          args: default
        metrics:
          - type: wer
            value: 0.1883670612192949
            name: Wer

TrainEsperanto

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

  • Loss: 0.0591
  • Wer: 0.1884

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: 32
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 30

Training results

Training Loss Epoch Step Validation Loss Wer
5.9902 2.6596 500 8.6294 1.0309
3.3 5.3191 1000 2.9688 1.0
2.8744 7.9787 1500 2.4117 1.0
0.7214 10.6383 2000 0.1825 0.2954
0.1552 13.2979 2500 0.0689 0.1971
0.1038 15.9574 3000 0.0621 0.1932
0.092 18.6170 3500 0.0624 0.1900
0.0877 21.2766 4000 0.0615 0.1926
0.082 23.9362 4500 0.0609 0.1899
0.0779 26.5957 5000 0.0591 0.1887
0.077 29.2553 5500 0.0591 0.1884

Framework versions

  • Transformers 4.45.2
  • Pytorch 2.5.1
  • Datasets 2.19.1
  • Tokenizers 0.20.1