---
library_name: transformers
language:
- sw
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- DigitalUmuganda/AfriVoice
metrics:
- wer
model-index:
- name: Whisper Small Hi - Sanchit Gandhi
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: AfriVoice
      type: DigitalUmuganda/AfriVoice
      args: 'config: sw, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 53.52916232990247
---

<!-- 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 Hi - Sanchit Gandhi

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the AfriVoice dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6526
- Wer: 53.5292

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step | Validation Loss | Wer     |
|:-------------:|:--------:|:----:|:---------------:|:-------:|
| 0.0002        | 153.8462 | 1000 | 1.4799          | 52.3072 |
| 0.0001        | 307.6923 | 2000 | 1.5528          | 52.1298 |
| 0.0           | 461.5385 | 3000 | 1.6058          | 52.3033 |
| 0.0           | 615.3846 | 4000 | 1.6294          | 52.8546 |
| 0.0           | 769.2308 | 5000 | 1.6526          | 53.5292 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.1.0+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1