---
library_name: transformers
language:
- wo
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper-WOLOF-5-hours-Google-Fleurs-dataset
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: google/fleurs
      type: google/fleurs
      config: wo_sn
      split: None
      args: 'config: wo, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 49.03357070193286
---

<!-- 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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/asr-africa-research-team/ASR%20Africa/runs/79l4ms4x)
# Whisper-WOLOF-5-hours-Google-Fleurs-dataset

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the google/fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5579
- Wer: 49.0336
- Cer: 18.1546

## 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: 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_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     | Cer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|:-------:|
| 0.7747        | 12.1951 | 500  | 1.3158          | 48.9318 | 18.0097 |
| 0.0052        | 24.3902 | 1000 | 1.4793          | 48.9431 | 18.1792 |
| 0.0012        | 36.5854 | 1500 | 1.5371          | 49.2144 | 18.0521 |
| 0.0008        | 48.7805 | 2000 | 1.5579          | 49.0336 | 18.1546 |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.1.0+cu118
- Datasets 3.0.1
- Tokenizers 0.20.1