metadata
library_name: transformers
language:
- pt
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Small pt - CV
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 17.0
type: mozilla-foundation/common_voice_17_0
config: pt
split: None
args: 'config: pt, split: test'
metrics:
- name: Wer
type: wer
value: 17.158573657375385
Whisper Small pt - CV
This model is a fine-tuned version of openai/whisper-small on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3521
- Wer: 17.1586
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
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 32
- total_eval_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1452 | 1.4556 | 1000 | 0.2624 | 17.9483 |
| 0.0733 | 2.9112 | 2000 | 0.2660 | 17.1344 |
| 0.0118 | 4.3668 | 3000 | 0.3177 | 17.2583 |
| 0.0066 | 5.8224 | 4000 | 0.3521 | 17.1586 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.8.0.dev20250515+cu128
- Datasets 3.6.0
- Tokenizers 0.21.1