metadata

license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - google/fleurs
metrics:
  - wer
model-index:
  - name: Whisper Medium Galician
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: google/fleurs gl_es
          type: google/fleurs
          config: gl_es
          split: test
          args: gl_es
        metrics:
          - name: Wer
            type: wer
            value: 14.674060048688126

Whisper Medium Galician

This model is a fine-tuned version of openai/whisper-medium on the google/fleurs gl_es dataset. It achieves the following results on the evaluation set:

Loss: 0.4553
Wer: 14.6741

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: 32
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
0.0002	39.01	1000	0.4553	14.6741
0.0001	79.0	2000	0.5023	14.9400
0.0	119.0	3000	0.5317	15.1609
0.0	159.0	4000	0.5513	15.2015
0.0	199.0	5000	0.5593	15.2060

Framework versions

Transformers 4.26.0.dev0
Pytorch 1.13.0+cu117
Datasets 2.7.1.dev0
Tokenizers 0.13.2