|
--- |
|
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: 26.192630898513254 |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# Whisper Base using Common Voice 16 (pt) |
|
|
|
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Mozilla Common Voices - 16.0 - Portuguese dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4574 |
|
- Wer: 26.1926 |
|
- Wer Normalized: 20.0029 |
|
|
|
## 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: 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: 500 |
|
- training_steps: 7000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | Wer Normalized | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:|:--------------:| |
|
| 0.4883 | 0.74 | 1000 | 0.3803 | 28.0317 | 21.8327 | |
|
| 0.2659 | 1.48 | 2000 | 0.3677 | 26.3688 | 20.1666 | |
|
| 0.1251 | 2.22 | 3000 | 0.3730 | 26.3752 | 20.4620 | |
|
| 0.1071 | 2.96 | 4000 | 0.3867 | 25.5026 | 19.5470 | |
|
| 0.0523 | 3.7 | 5000 | 0.4148 | 25.7094 | 19.6851 | |
|
| 0.02 | 4.44 | 6000 | 0.4491 | 25.6803 | 19.5759 | |
|
| 0.0134 | 5.18 | 7000 | 0.4574 | 26.1926 | 20.0029 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.36.2 |
|
- Pytorch 2.1.1 |
|
- Datasets 2.16.1 |
|
- Tokenizers 0.15.0 |
|
|