---
library_name: transformers
language:
- am
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- leyu-amharic/leyu-amharic-wello-dialect
metrics:
- wer
model-index:
- name: Whisper Small Wello
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Leyu Amharic Wello Dialect
      type: leyu-amharic/leyu-amharic-wello-dialect
    metrics:
    - name: Wer
      type: wer
      value: 70.49579459938026
---

<!-- 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 Wello

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Leyu Amharic Wello Dialect dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3457
- Wer Ortho: 74.3326
- Wer: 70.4958

## 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: 5e-06
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:-------:|
| 0.0950        | 3.3333  | 500  | 0.2847          | 75.4209   | 71.9345 |
| 0.0280        | 6.6667  | 1000 | 0.3072          | 74.0246   | 70.4737 |
| 0.0107        | 10.0    | 1500 | 0.3337          | 74.1889   | 70.2966 |
| 0.0028        | 13.3333 | 2000 | 0.3457          | 74.3326   | 70.4958 |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2