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whisper-atco2-large

Automatic Speech Recognition
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whisper
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whisper-atco2-large / README.md
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - wer
base_model: openai/whisper-large
model-index:
  - name: openai/whisper-large
    results: []

openai/whisper-large

This model is a fine-tuned version of openai/whisper-large on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6750
  • Wer: 16.9811

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: 4
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 8
  • 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: 200
  • training_steps: 500
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.1978 2.01 100 0.5474 21.0692
0.0087 4.02 200 0.6202 19.4969
0.0029 6.04 300 0.6264 18.2390
0.0003 8.05 400 0.6659 17.1908
0.0002 10.06 500 0.6750 16.9811

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.1+cu117
  • Datasets 2.7.1.dev0
  • Tokenizers 0.13.2