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whisper-small-CV_Fleurs_AMMI_ALFFA-sw-1hrs-v1

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metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: whisper-small-CV_Fleurs_AMMI_ALFFA-sw-1hrs-v1
    results: []

whisper-small-CV_Fleurs_AMMI_ALFFA-sw-1hrs-v1

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

  • Loss: 2.0750
  • Wer: 0.6608
  • Cer: 0.3094

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: 4
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 8
  • optimizer: Use OptimizerNames.ADAMW_HF with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 100
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
2.8725 1.0 72 1.4755 0.9300 0.3706
0.9122 2.0 144 1.2054 0.7693 0.3183
0.4127 3.0 216 1.1717 0.6751 0.2664
0.2043 4.0 288 1.2860 0.7312 0.3201
0.1703 5.0 360 1.3121 0.5544 0.2231
0.1509 6.0 432 1.3884 0.5587 0.2045
0.1646 7.0 504 1.5089 0.6426 0.2695
0.1761 8.0 576 1.5317 0.5963 0.2422
0.1725 9.0 648 1.5984 0.5842 0.2437
0.1968 10.0 720 1.7078 0.6239 0.2540
0.1949 11.0 792 1.8013 0.6542 0.2965
0.1738 12.0 864 1.8570 0.9835 0.6013
0.1511 13.0 936 1.9424 0.6105 0.2695
0.1478 14.0 1008 1.8473 0.7972 0.3916
0.127 15.0 1080 1.8845 0.7513 0.3836
0.1058 16.0 1152 2.0406 0.6778 0.3159
0.0982 17.0 1224 2.0612 0.6522 0.3179
0.0938 18.0 1296 2.0644 0.6445 0.3006
0.0832 19.0 1368 2.0671 0.8840 0.4900
0.0787 20.0 1440 2.0750 0.6608 0.3094

Framework versions

  • Transformers 4.48.0
  • Pytorch 2.5.1+cu124
  • Datasets 3.2.0
  • Tokenizers 0.21.0