---
library_name: transformers
language:
- bem
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- BIG-C/BEMBA
metrics:
- wer
model-index:
- name: Whisper Small Bemba - Beijuka Bruno
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: BEMBA
      type: BIG-C/BEMBA
      args: 'config: bemba, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 0.4524958367137794
---

<!-- 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 Bemba - Beijuka Bruno

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the BEMBA dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1631
- Model Preparation Time: 0.0092
- Wer: 0.4525
- Cer: 0.1227

## 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: 4
- 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
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Model Preparation Time | Wer    | Cer    |
|:-------------:|:-----:|:-----:|:---------------:|:----------------------:|:------:|:------:|
| 1.1298        | 1.0   | 1281  | 0.8440          | 0.0092                 | 0.5704 | 0.1924 |
| 0.6239        | 2.0   | 2562  | 0.7778          | 0.0092                 | 0.5489 | 0.1840 |
| 0.4117        | 3.0   | 3843  | 0.7974          | 0.0092                 | 0.5208 | 0.1680 |
| 0.2409        | 4.0   | 5124  | 0.8600          | 0.0092                 | 0.5432 | 0.1883 |
| 0.1249        | 5.0   | 6405  | 0.9344          | 0.0092                 | 0.5202 | 0.1696 |
| 0.0619        | 6.0   | 7686  | 1.0230          | 0.0092                 | 0.5079 | 0.1667 |
| 0.0349        | 7.0   | 8967  | 1.0739          | 0.0092                 | 0.5135 | 0.1649 |
| 0.0232        | 8.0   | 10248 | 1.1178          | 0.0092                 | 0.5039 | 0.1673 |
| 0.0173        | 9.0   | 11529 | 1.1459          | 0.0092                 | 0.5154 | 0.1670 |
| 0.0139        | 10.0  | 12810 | 1.2013          | 0.0092                 | 0.5139 | 0.1672 |
| 0.0124        | 11.0  | 14091 | 1.2302          | 0.0092                 | 0.5133 | 0.1658 |
| 0.011         | 12.0  | 15372 | 1.2629          | 0.0092                 | 0.5142 | 0.1732 |
| 0.0084        | 13.0  | 16653 | 1.3002          | 0.0092                 | 0.5135 | 0.1650 |
| 0.0075        | 14.0  | 17934 | 1.3475          | 0.0092                 | 0.4972 | 0.1629 |
| 0.0081        | 15.0  | 19215 | 1.3522          | 0.0092                 | 0.4931 | 0.1618 |
| 0.0077        | 16.0  | 20496 | 1.3592          | 0.0092                 | 0.5087 | 0.1623 |
| 0.0073        | 17.0  | 21777 | 1.3655          | 0.0092                 | 0.5067 | 0.1662 |
| 0.0061        | 18.0  | 23058 | 1.3930          | 0.0092                 | 0.5074 | 0.1669 |
| 0.0057        | 19.0  | 24339 | 1.3912          | 0.0092                 | 0.5055 | 0.1636 |
| 0.0065        | 20.0  | 25620 | 1.4236          | 0.0092                 | 0.4995 | 0.1641 |
| 0.0052        | 21.0  | 26901 | 1.4587          | 0.0092                 | 0.5035 | 0.1609 |
| 0.0044        | 22.0  | 28182 | 1.4459          | 0.0092                 | 0.5034 | 0.1653 |
| 0.006         | 23.0  | 29463 | 1.4685          | 0.0092                 | 0.5036 | 0.1684 |
| 0.0051        | 24.0  | 30744 | 1.4455          | 0.0092                 | 0.5029 | 0.1651 |
| 0.0043        | 25.0  | 32025 | 1.4682          | 0.0092                 | 0.5410 | 0.1875 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.1.0+cu118
- Datasets 3.0.0
- Tokenizers 0.19.1