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---
language:
- yo
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
metrics:
- wer
model-index:
- name: Whisper Small Yo - Oyemade Oyemaja
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 16
type: mozilla-foundation/common_voice_16_1
config: yo
split: test
args: yo
metrics:
- name: Wer
type: wer
value: 49.86116954143879
---
<!-- 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 Yo - Oyemade Oyemaja
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 16 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1731
- Wer Ortho: 70.4834
- Wer: 49.8612
## 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: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:-------:|
| 0.2595 | 3.8462 | 500 | 0.7546 | 71.3700 | 52.0488 |
| 0.0312 | 7.6923 | 1000 | 0.9057 | 74.6210 | 53.1174 |
| 0.0134 | 11.5385 | 1500 | 1.0199 | 72.2090 | 51.7711 |
| 0.0059 | 15.3846 | 2000 | 1.0713 | 71.2842 | 51.6281 |
| 0.0087 | 19.2308 | 2500 | 1.1007 | 70.5787 | 50.1136 |
| 0.006 | 23.0769 | 3000 | 1.1568 | 70.8552 | 50.6100 |
| 0.0059 | 26.9231 | 3500 | 1.1327 | 69.0438 | 48.4645 |
| 0.0043 | 30.7692 | 4000 | 1.1731 | 70.4834 | 49.8612 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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