transformers pytorch tensorboard whisper automatic-speech-recognition generated_from_trainer dataset:mozilla-foundation/common_voice_16_0 base_model:openai/whisper-base license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-base-common-voice-16-pt
  results: []
datasets:
- mozilla-foundation/common_voice_16_0
---

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# whisper-base-common-voice-16-pt

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3608
- Wer: 25.7805
- Wer Normalized: 19.8889

## 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: 2.05e-05
- train_batch_size: 16
- 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: 300
- training_steps: 3000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     | Wer Normalized |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:--------------:|
| 0.4466        | 0.37  | 500  | 0.4422          | 30.9405 | 25.0028        |
| 0.3661        | 0.74  | 1000 | 0.4012          | 29.2259 | 22.9756        |
| 0.1767        | 1.11  | 1500 | 0.3841          | 27.5178 | 21.3383        |
| 0.1896        | 1.48  | 2000 | 0.3698          | 26.7728 | 20.5807        |
| 0.1637        | 1.85  | 2500 | 0.3616          | 25.5398 | 20.0286        |
| 0.1033        | 2.22  | 3000 | 0.3608          | 25.7805 | 19.8889        |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.1
- Datasets 2.16.1
- Tokenizers 0.15.0