metadata

license: apache-2.0
base_model: openai/whisper-base
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: whisper-base-google-fleurs-pt-br
    results: []

whisper-base-google-fleurs-pt-br

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

Loss: 0.4987
Wer: 22.2974
Wer Normalized: 18.5291

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: 2.05e-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: reduce_lr_on_plateau
lr_scheduler_warmup_steps: 120
training_steps: 2400
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Wer Normalized
0.3716	1.01	400	0.3988	21.8039	17.8916
0.2003	2.02	800	0.4440	22.3350	18.6242
0.0571	3.02	1200	0.4960	22.5982	19.2284
0.03	4.03	1600	0.4987	22.2974	18.5291

Framework versions

Transformers 4.36.2
Pytorch 2.1.1
Datasets 2.16.1
Tokenizers 0.15.0