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metadata
language:
  - de
license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: openai/whisper-tiny
    results: []

openai/whisper-tiny

This model is a fine-tuned version of openai/whisper-tiny on the Hanhpt23/GermanMed dataset. It achieves the following results on the evaluation set:

  • Loss: 5.8433
  • Wer: 107.4053

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: 0.0001
  • train_batch_size: 8
  • 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: 100
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Wer
3.2151 1.0 765 3.6892 145.0057
2.4608 2.0 1530 3.7770 102.6980
1.8089 3.0 2295 4.0128 125.0287
1.3185 4.0 3060 4.2434 104.7072
0.8036 5.0 3825 4.5708 111.1940
0.464 6.0 4590 4.7913 128.3582
0.2689 7.0 5355 4.9963 117.8530
0.1899 8.0 6120 5.1768 108.7256
0.192 9.0 6885 5.2917 103.8462
0.128 10.0 7650 5.4184 105.2813
0.1435 11.0 8415 5.5027 115.8439
0.1201 12.0 9180 5.6452 110.9070
0.1328 13.0 9945 5.6889 122.4455
0.0979 14.0 10710 5.6940 113.2032
0.1165 15.0 11475 5.7213 108.5534
0.0978 16.0 12240 5.7604 105.7405
0.0927 17.0 13005 5.7672 105.9127
0.0829 18.0 13770 5.7777 106.1998
0.0974 19.0 14535 5.7957 110.3904
0.0998 20.0 15300 5.8433 107.4053

Framework versions

  • Transformers 4.41.1
  • Pytorch 2.3.0
  • Datasets 2.19.1
  • Tokenizers 0.19.1