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---
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- babs/nigerian-accented-english
metrics:
- wer
model-index:
- name: Whisper Small english - Nigerian accent
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Nigerian accented english
type: babs/nigerian-accented-english
args: 'config: en, split: test'
metrics:
- name: Wer
type: wer
value: 48.805954719321825
---
<!-- 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 english - Nigerian accent
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Nigerian accented english dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3324
- Wer: 48.8060
## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.3217 | 4.6948 | 1000 | 0.8267 | 55.4637 |
| 0.0653 | 9.3897 | 2000 | 1.0964 | 53.9440 |
| 0.0161 | 14.0845 | 3000 | 1.2460 | 51.9901 |
| 0.0044 | 18.7793 | 4000 | 1.3324 | 48.8060 |
### Framework versions
- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0
|