---
language:
- sw
license: apache-2.0
base_model: openai/whisper-large
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_14_0
metrics:
- wer
model-index:
- name: Whisper small  - Denis Musinguzi
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 14.0
      type: mozilla-foundation/common_voice_14_0
      config: sw
      split: None
      args: 'config: sw, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 0.25130933149495305
---

<!-- 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  - Denis Musinguzi

This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co./openai/whisper-large) on the Common Voice 14.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4428
- Wer: 0.2513
- Cer: 0.0983

## 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: 32
- eval_batch_size: 32
- 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: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Cer    | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:------:|:---------------:|:------:|
| 0.9179        | 0.51  | 800  | 0.1412 | 0.5355          | 0.3693 |
| 0.3078        | 1.02  | 1600 | 0.1196 | 0.4343          | 0.3152 |
| 0.1959        | 1.53  | 2400 | 0.1172 | 0.4068          | 0.2822 |
| 0.1737        | 2.04  | 3200 | 0.1145 | 0.3922          | 0.2721 |
| 0.1046        | 2.55  | 4000 | 0.1084 | 0.3958          | 0.2634 |
| 0.1019        | 3.06  | 4800 | 0.1029 | 0.3957          | 0.2578 |
| 0.0588        | 3.57  | 5600 | 0.1132 | 0.4013          | 0.2666 |
| 0.0545        | 4.08  | 6400 | 0.1009 | 0.4112          | 0.2510 |
| 0.0305        | 4.59  | 7200 | 0.0941 | 0.4183          | 0.2442 |
| 0.0275        | 5.1   | 8000 | 0.1005 | 0.4303          | 0.2549 |
| 0.0153        | 5.61  | 8800 | 0.4374 | 0.2407          | 0.0908 |
| 0.014         | 6.12  | 9600 | 0.4428 | 0.2513          | 0.0983 |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.2.1
- Datasets 2.17.0
- Tokenizers 0.15.2