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---
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
---
<!-- 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 Small Portuguese
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/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
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