metadata

language:
  - pt
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: Whisper Small Portuguese
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_11_0 pt
          type: mozilla-foundation/common_voice_11_0
          config: pt
          split: test
          args: pt
        metrics:
          - name: Wer
            type: wer
            value: 14.884437596302003

Whisper Small Portuguese

This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_11_0 pt dataset. It achieves the following results on the evaluation set:

Loss: 0.3191
Wer: 14.8844
Cer: 5.7447

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: 5e-06
train_batch_size: 32
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1000
training_steps: 10000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
2.9379	0.92	500	0.4783	17.3806	7.0572
2.1727	1.84	1000	0.3721	17.2727	6.7975
1.7856	2.76	1500	0.3466	16.3790	6.4023
1.7803	3.68	2000	0.3372	15.9014	6.2089
1.8312	4.6	2500	0.3303	15.7473	6.0901
1.6403	5.52	3000	0.3256	15.9476	6.1896
1.536	6.45	3500	0.3235	15.5008	6.0928
1.4223	7.37	4000	0.3209	15.3621	6.0735
1.4652	8.29	4500	0.3209	15.2696	5.9326
1.2572	9.21	5000	0.3191	14.8844	5.7447
1.7142	10.13	5500	0.3182	15.0077	5.8469
1.4195	11.05	6000	0.3171	15.0693	5.8856
1.3965	11.97	6500	0.3167	15.0539	5.8580

Framework versions

Transformers 4.26.0.dev0
Pytorch 1.12.1+cu116
Datasets 2.7.1.dev0
Tokenizers 0.13.2