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metadata
license: apache-2.0
base_model: openai/whisper-base.en
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: abbenedekwhisper-base.en-finetuning3-D3K
    results: []

abbenedekwhisper-base.en-finetuning3-D3K

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

  • Loss: 3.3880
  • Cer: 68.1692
  • Wer: 115.5629
  • Ser: 100.0
  • Cer Clean: 3.6171
  • Wer Clean: 6.2914
  • Ser Clean: 7.0175

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: 5e-08
  • train_batch_size: 16
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 10
  • training_steps: 2000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Cer Wer Ser Cer Clean Wer Clean Ser Clean
7.3491 1.06 200 6.1358 64.7746 122.5166 100.0 3.2832 5.6291 7.0175
6.162 2.13 400 5.2935 64.2181 119.8675 100.0 3.7284 6.6225 7.8947
5.3192 3.19 600 4.7534 64.6633 119.2053 100.0 3.5058 6.2914 7.0175
4.7266 4.26 800 4.3761 65.1085 118.2119 100.0 3.2832 5.9603 6.1404
4.2728 5.32 1000 4.0472 65.9432 117.2185 100.0 3.2276 5.9603 6.1404
3.9248 6.38 1200 3.7904 66.7223 116.2252 100.0 3.2276 5.9603 6.1404
3.6714 7.45 1400 3.6008 67.8909 117.2185 100.0 3.1720 5.9603 6.1404
3.499 8.51 1600 3.4790 69.0595 118.2119 100.0 3.1720 5.9603 6.1404
3.393 9.57 1800 3.4106 68.9482 117.5497 100.0 3.1720 5.9603 6.1404
3.3491 10.64 2000 3.3880 68.1692 115.5629 100.0 3.6171 6.2914 7.0175

Framework versions

  • Transformers 4.39.3
  • Pytorch 2.2.2+cu121
  • Datasets 2.14.5
  • Tokenizers 0.15.2