---
library_name: transformers
language:
- en
license: apache-2.0
base_model: EYEDOL/english-ASR
tags:
- whisper-event
- generated_from_trainer
datasets:
- okezieowen/misc_naija_english_audio
metrics:
- wer
model-index:
- name: English_ASR2
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: misc_naija_english
      type: okezieowen/misc_naija_english_audio
    metrics:
    - name: Wer
      type: wer
      value: 0.8855441714268444
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# English_ASR2

This model is a fine-tuned version of [EYEDOL/english-ASR](https://huggingface.co/EYEDOL/english-ASR) on the misc_naija_english dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0001
- Wer: 0.8855

## 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: 8
- 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: 3000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.0001        | 8.9286 | 3000 | 0.0001          | 0.8855 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1