metadata

library_name: transformers
language:
  - en
license: apache-2.0
base_model: openai/whisper-medium.en
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_17_0
metrics:
  - wer
model-index:
  - name: whisper-medium-en-cv-4.2
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 17.0
          type: mozilla-foundation/common_voice_17_0
          config: en
          split: test
          args: 'config: en, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 13.345521023765997

whisper-medium-en-cv-4.2

This model is a fine-tuned version of openai/whisper-medium.en on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:

Loss: 0.5540
Wer: 13.3455

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: 32
eval_batch_size: 64
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1000
training_steps: 13500
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2332	0.1667	2250	0.4139	12.7057
0.0826	1.1667	4500	0.4543	14.2596
0.0267	2.1667	6750	0.4961	14.5338
0.0066	3.1667	9000	0.5053	14.6252
0.0019	4.1667	11250	0.5349	13.9854
0.0011	5.1667	13500	0.5540	13.3455

Framework versions

Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1