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whisper-atco2-medium

This model is a fine-tuned version of openai/whisper-medium on the luigisaetta/atco2_normalized_augmented dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6129
  • Wer: 17.5052

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: 2
  • eval_batch_size: 1
  • seed: 42
  • gradient_accumulation_steps: 16
  • 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
2.3939 1.06 50 1.8493 66.5618
0.5127 2.13 100 0.5119 30.6080
0.0626 3.19 150 0.5410 20.4403
0.0157 4.25 200 0.5775 19.8113
0.0107 5.32 250 0.5552 19.7065
0.0044 6.38 300 0.5723 18.1342
0.0013 7.45 350 0.5763 17.7149
0.0005 8.51 400 0.6053 17.7149
0.0004 9.57 450 0.6109 17.5052
0.0004 10.64 500 0.6129 17.5052

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.0+cu117
  • Datasets 2.7.1.dev0
  • Tokenizers 0.11.0
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Dataset used to train luigisaetta/whisper-atco2-medium

Evaluation results