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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: whisper-small-pt-cv11-v4_2
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_11_0
      type: common_voice_11_0
      config: pt
      split: test
      args: pt
    metrics:
    - name: Wer
      type: wer
      value: 14.28351309707242
---

<!-- 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-pt-cv11-v4_2

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the common_voice_11_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2995
- Wer: 14.2835
- Cer: 5.5623

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|
| 1.1113        | 0.92  | 500  | 0.3897          | 16.8721 | 6.7919 |
| 0.9009        | 1.84  | 1000 | 0.3318          | 15.9322 | 6.2310 |
| 0.7631        | 2.76  | 1500 | 0.3177          | 15.4854 | 5.8939 |
| 0.7163        | 3.68  | 2000 | 0.3130          | 14.8998 | 5.7972 |
| 0.6334        | 4.6   | 2500 | 0.3034          | 14.7920 | 5.6867 |
| 0.5746        | 5.52  | 3000 | 0.3029          | 14.6225 | 5.6397 |
| 0.5359        | 6.45  | 3500 | 0.3018          | 14.4838 | 5.5789 |
| 0.5058        | 7.37  | 4000 | 0.3010          | 14.5917 | 5.6839 |
| 0.4833        | 8.29  | 4500 | 0.3023          | 14.2373 | 5.5236 |
| 0.4398        | 9.21  | 5000 | 0.3005          | 14.4222 | 5.5844 |
| 0.4359        | 10.13 | 5500 | 0.2999          | 14.4838 | 5.6259 |
| 0.4036        | 11.05 | 6000 | 0.2995          | 14.2835 | 5.5623 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.12.1+cu116
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2