metadata
language:
- pt
license: apache-2.0
base_model: openai/whisper-base
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
metrics:
- wer
model-index:
- name: Whisper Base using Common Voice 16 (pt)
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Mozilla Common Voices - 16.0 - Portuguese
type: mozilla-foundation/common_voice_16_0
config: pt
split: test
args: pt
metrics:
- name: Wer
type: wer
value: 25.436328377504847
Whisper Base using Common Voice 16 (pt)
This model is a fine-tuned version of openai/whisper-base on the Mozilla Common Voices - 16.0 - Portuguese dataset. It achieves the following results on the evaluation set:
- Loss: 0.3552
- Wer: 25.4363
- Wer Normalized: 19.4668
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: 2e-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: 400
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Wer Normalized |
|---|---|---|---|---|---|
| 0.6085 | 0.19 | 500 | 0.4465 | 32.1833 | 25.3383 |
| 0.4624 | 0.37 | 1000 | 0.4131 | 28.9867 | 22.8488 |
| 0.4375 | 0.56 | 1500 | 0.3936 | 27.8135 | 21.3817 |
| 0.4372 | 0.74 | 2000 | 0.3784 | 27.5695 | 21.7171 |
| 0.4704 | 0.93 | 2500 | 0.3630 | 26.1167 | 20.5133 |
| 0.2013 | 1.11 | 3000 | 0.3600 | 25.5462 | 19.7750 |
| 0.2261 | 1.3 | 3500 | 0.3570 | 25.5010 | 19.5181 |
| 0.2118 | 1.48 | 4000 | 0.3552 | 25.4363 | 19.4668 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.1
- Datasets 2.16.1
- Tokenizers 0.15.0