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Baseline-FT

Automatic Speech Recognition
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metadata
license: apache-2.0
base_model: openai/whisper-small.en
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: 2024-02-22_22-55-48
    results: []

2024-02-22_22-55-48

This model is a fine-tuned version of openai/whisper-small.en on 135h of the MyST dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2345
  • Wer: 8.9883

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: 1e-05
  • train_batch_size: 64
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • training_steps: 0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.3157 1.0 907 0.2345 8.9883

Framework versions

  • Transformers 4.37.2
  • Pytorch 1.13.1+cu116
  • Datasets 2.17.0
  • Tokenizers 0.15.2