---
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: None
      args: gn
    metrics:
    - name: Wer
      type: wer
      value: 56.50474595198214
---

<!-- 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: 0.5052
- Wer: 56.5047

## 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: 2e-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: 500
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer      |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 4.2519        | 0.0991 | 100  | 2.0016          | 176.2144 |
| 1.9569        | 0.1982 | 200  | 1.0866          | 92.1273  |
| 1.3814        | 0.2973 | 300  | 0.8375          | 77.2194  |
| 1.0866        | 0.3964 | 400  | 0.7128          | 69.4026  |
| 0.8892        | 0.4955 | 500  | 0.6427          | 68.7326  |
| 0.7668        | 0.5946 | 600  | 0.5942          | 65.7175  |
| 0.698         | 0.6938 | 700  | 0.5732          | 60.9715  |
| 0.593         | 0.7929 | 800  | 0.5278          | 57.5656  |
| 0.5585        | 0.8920 | 900  | 0.5330          | 60.2457  |
| 0.5199        | 0.9911 | 1000 | 0.5052          | 56.5047  |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1