---
language:
- sw
license: apache-2.0
base_model: openai/whisper-medium
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_14_0
metrics:
- wer
model-index:
- name: Whisper Medium  - 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: lg
      split: None
      args: 'config: sw, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 0.2354584169666847
---

<!-- 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 Medium  - Denis Musinguzi

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co./openai/whisper-medium) on the Common Voice 14.0 dataset.
It achieves the following results on the evaluation set:
- Cer: 0.0622
- Loss: 0.2969
- Wer: 0.2355

## 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: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Cer    | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:------:|:---------------:|:------:|
| 0.9513        | 0.3   | 800  | 0.0998 | 0.4428          | 0.4067 |
| 0.313         | 0.61  | 1600 | 0.0913 | 0.3519          | 0.3427 |
| 0.2593        | 0.91  | 2400 | 0.0628 | 0.3160          | 0.2689 |
| 0.1887        | 1.22  | 3200 | 0.0633 | 0.3049          | 0.2574 |
| 0.1642        | 1.52  | 4000 | 0.0752 | 0.2906          | 0.2655 |
| 0.1595        | 1.82  | 4800 | 0.0737 | 0.2807          | 0.2617 |
| 0.1288        | 2.13  | 5600 | 0.0643 | 0.2889          | 0.2416 |
| 0.0928        | 2.43  | 6400 | 0.0629 | 0.2860          | 0.2387 |
| 0.0887        | 2.74  | 7200 | 0.0572 | 0.2838          | 0.2309 |
| 0.0836        | 3.04  | 8000 | 0.0575 | 0.2897          | 0.2338 |
| 0.0466        | 3.34  | 8800 | 0.0572 | 0.2968          | 0.2322 |
| 0.045         | 3.65  | 9600 | 0.0622 | 0.2969          | 0.2355 |


### Framework versions

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