---
language:
- gn
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
metrics:
- wer
model-index:
- name: Common Voice 16 - Guarani
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 16
      type: mozilla-foundation/common_voice_16_1
      config: gn
      split: test
      args: gn
    metrics:
    - name: Wer
      type: wer
      value: 64.48061273336525
---

<!-- 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. -->

# Common Voice 16 - Guarani

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Common Voice 16 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5847
- Wer: 64.4806

## 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-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 2.4447        | 0.7692 | 100  | 0.9750          | 88.2001 |
| 0.6471        | 1.5385 | 200  | 0.7163          | 74.5811 |
| 0.3822        | 2.3077 | 300  | 0.6274          | 66.7066 |
| 0.2487        | 3.0769 | 400  | 0.6025          | 66.4911 |
| 0.1549        | 3.8462 | 500  | 0.5847          | 64.4806 |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1