metadata

language:
  - en
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - simodo79/Vaudeville
metrics:
  - wer
model-index:
  - name: Whisper Small Vdv
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Vaudeville
          type: simodo79/Vaudeville
          config: default
          split: None
          args: 'config: en, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 0
pipeline_tag: automatic-speech-recognition
library_name: transformers

Whisper Small Vdv

This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

Loss: 0.0000
Wer: 0.0

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: 16
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: 500
training_steps: 5000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0	500.0	1000	0.0000	0.0
0.0	1000.0	2000	0.0000	0.0
0.0	1500.0	3000	0.0000	0.0
0.0	2000.0	4000	0.0000	0.0
0.0	2500.0	5000	0.0000	0.0

Framework versions

Transformers 4.43.3
Pytorch 1.12.0
Datasets 2.20.0
Tokenizers 0.19.1