---
library_name: transformers
language:
- ee
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- dodziraynard/ugspeechdata-ewe
metrics:
- wer
model-index:
- name: UG Speech Data ASR - Ewe nornmaliser
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: ugspeechdata-ewe
      type: dodziraynard/ugspeechdata-ewe
    metrics:
    - name: Wer
      type: wer
      value: 38.68761412051126
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# UG Speech Data ASR - Ewe nornmaliser

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the ugspeechdata-ewe dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5275
- Wer Ortho: 46.3552
- Wer: 38.6876
- Cer: 13.2130

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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 | Cer     | Validation Loss | Wer     | Wer Ortho |
|:-------------:|:------:|:----:|:-------:|:---------------:|:-------:|:---------:|
| 0.5021        | 0.4785 | 400  | 15.1787 | 0.5774          | 44.6759 | 52.4914   |
| 0.4833        | 0.9569 | 800  | 13.7387 | 0.5141          | 40.5820 | 48.5622   |
| 0.3765        | 1.4354 | 1200 | 13.0650 | 0.4926          | 38.5423 | 46.8196   |
| 0.3626        | 1.9139 | 1600 | 12.9516 | 0.4771          | 37.9238 | 46.1237   |
| 0.3109        | 2.3923 | 2000 | 12.3654 | 0.4750          | 37.0070 | 44.9041   |
| 0.3048        | 2.8708 | 2400 | 12.9748 | 0.4719          | 37.5137 | 45.5116   |
| 0.2446        | 3.3493 | 2800 | 0.4953  | 45.7020         | 37.8667 | 12.8493   |
| 0.2362        | 3.8278 | 3200 | 0.4882  | 45.9007         | 38.0896 | 13.0340   |
| 0.1642        | 4.3062 | 3600 | 0.5249  | 46.3910         | 38.3491 | 12.8627   |
| 0.1611        | 4.7847 | 4000 | 0.5275  | 46.3552         | 38.6876 | 13.2130   |


### Framework versions

- Transformers 4.48.0
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.2