metadata

library_name: transformers
language:
  - yo
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_17_0
metrics:
  - wer
model-index:
  - name: Whisper Small yo - harcuracy model
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 17.0
          type: mozilla-foundation/common_voice_17_0
          config: yo
          split: test
          args: 'config: yo, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 75.33815964945704

Whisper Small yo - harcuracy model

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

Loss: 1.2762
Wer: 75.3382

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: 8
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
training_steps: 1500
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1066	5.5556	500	0.9370	76.7003
0.0053	11.1111	1000	1.1919	74.9571
0.0012	16.6667	1500	1.2762	75.3382

Framework versions

Transformers 4.47.0
Pytorch 2.4.0
Datasets 3.2.0
Tokenizers 0.21.0