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Whisper Base ATCOSIM

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

  • Loss: 0.5964
  • Wer: 404.9337

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: 16
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 1000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
8.7316 0.2092 100 8.1521 110.7020
5.3768 0.4184 200 5.2758 110.9713
3.2842 0.6276 300 3.4243 119.1492
1.892 0.8368 400 2.1743 121.4377
0.9999 1.0460 500 1.4513 168.8160
0.6472 1.2552 600 1.0157 369.7449
0.529 1.4644 700 0.8372 356.8554
0.4086 1.6736 800 0.6973 300.4644
0.3559 1.8828 900 0.6164 361.0150
0.2302 2.0921 1000 0.5964 404.9337

Framework versions

  • Transformers 4.42.0.dev0
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.2
  • Tokenizers 0.19.1
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Dataset used to train allenpoe/whisper-small-finetuned-atcosim-model

Evaluation results