---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-small-yoruba-07-17
  results: []
---

<!-- 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. -->

# whisper-small-yoruba-07-17

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3346
- Wer Ortho: 34.5068
- Wer: 25.6765

## 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: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| 0.7951        | 0.0745 | 250  | 0.8000          | 60.4651   | 45.9597 |
| 0.605         | 0.1490 | 500  | 0.6408          | 50.3176   | 39.3120 |
| 0.5273        | 0.2235 | 750  | 0.5621          | 45.8657   | 35.7526 |
| 0.4483        | 0.2980 | 1000 | 0.5138          | 43.4349   | 33.8902 |
| 0.4158        | 0.3725 | 1250 | 0.4752          | 41.9130   | 32.5295 |
| 0.4032        | 0.4470 | 1500 | 0.4434          | 41.1866   | 31.6249 |
| 0.3261        | 0.5215 | 1750 | 0.4153          | 40.2187   | 30.3193 |
| 0.3606        | 0.5959 | 2000 | 0.3910          | 38.0659   | 29.1049 |
| 0.3008        | 0.6704 | 2250 | 0.3769          | 36.7084   | 27.5409 |
| 0.2938        | 0.7449 | 2500 | 0.3608          | 36.2985   | 27.0924 |
| 0.2933        | 0.8194 | 2750 | 0.3494          | 35.6086   | 27.0448 |
| 0.277         | 0.8939 | 3000 | 0.3404          | 34.5474   | 25.5682 |
| 0.2849        | 0.9684 | 3250 | 0.3346          | 34.5068   | 25.6765 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1