---
language:
- pt
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Large-V3 Portuguese
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_13_0 pt
      type: mozilla-foundation/common_voice_13_0
      config: pt
      split: test
      args: pt
    metrics:
    - name: Wer
      type: wer
      value: 4.600269444353169
---

<!-- 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 Large-V3 Portuguese

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on the mozilla-foundation/common_voice_13_0 pt dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4315
- Wer: 4.6003

## 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-06
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 20000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.0702        | 3.53  | 1000  | 0.1289          | 4.0367 |
| 0.0247        | 7.05  | 2000  | 0.1806          | 4.4294 |
| 0.0074        | 10.58 | 3000  | 0.2821          | 4.7481 |
| 0.0022        | 14.11 | 4000  | 0.3160          | 4.6249 |
| 0.0016        | 17.64 | 5000  | 0.3261          | 4.6479 |
| 0.0027        | 21.16 | 6000  | 0.3373          | 4.6479 |
| 0.0009        | 24.69 | 7000  | 0.3642          | 4.7087 |
| 0.0007        | 28.22 | 8000  | 0.3551          | 4.6611 |
| 0.0006        | 31.75 | 9000  | 0.3741          | 4.7481 |
| 0.0004        | 35.27 | 10000 | 0.3755          | 4.6791 |
| 0.0008        | 38.8  | 11000 | 0.3690          | 4.6381 |
| 0.0002        | 42.33 | 12000 | 0.3888          | 4.5115 |
| 0.0002        | 45.86 | 13000 | 0.3982          | 4.5855 |
| 0.0001        | 49.38 | 14000 | 0.4040          | 4.6085 |
| 0.0001        | 52.91 | 15000 | 0.4100          | 4.5888 |
| 0.0001        | 56.44 | 16000 | 0.4165          | 4.5871 |
| 0.0001        | 59.96 | 17000 | 0.4211          | 4.5855 |
| 0.0001        | 63.49 | 18000 | 0.4265          | 4.5838 |
| 0.0001        | 67.02 | 19000 | 0.4302          | 4.5921 |
| 0.0001        | 70.55 | 20000 | 0.4315          | 4.6003 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.15.1