transformers tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer dataset:mozilla-foundation/common_voice_16_0 base_model:openai/whisper-large-v3 license:apache-2.0 model-index endpoints_compatible region:us
---
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
metrics:
- wer
model-index:
- name: whisper-large-v3-pt-cv16-cuda
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_16_0 pt
      type: mozilla-foundation/common_voice_16_0
      split: None
      args: pt
    metrics:
    - name: Wer
      type: wer
      value: 0.9998545572074984
---

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# whisper-large-v3-pt-cv16-cuda

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_16_0 pt dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1325
- Wer: 0.9999

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.199         | 0.26  | 1000 | 0.1563          | 0.1124 |
| 0.1654        | 0.52  | 2000 | 0.1500          | 0.1052 |
| 0.1794        | 0.77  | 3000 | 0.1379          | 0.0997 |
| 0.0821        | 1.03  | 4000 | 0.1321          | 1.0007 |
| 0.1292        | 1.29  | 5000 | 0.1325          | 0.9999 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.2.0.dev20231212
- Datasets 2.15.1.dev0
- Tokenizers 0.15.0
