---
library_name: transformers
language:
- sw
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: stt-april-1
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 17
      type: mozilla-foundation/common_voice_17_0
    metrics:
    - name: Wer
      type: wer
      value: 26.149347116430903
---

<!-- 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. -->

# stt-april-1

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 17 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7422
- Wer Ortho: 32.1876
- Wer: 26.1493

## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-------:|:-----:|:---------------:|:---------:|:-------:|
| 0.6457        | 0.6180  | 500   | 0.6308          | 38.7728   | 31.6649 |
| 0.3566        | 1.2361  | 1000  | 0.5699          | 36.3837   | 29.0941 |
| 0.3687        | 1.8541  | 1500  | 0.5554          | 34.7230   | 27.5095 |
| 0.2412        | 2.4722  | 2000  | 0.5469          | 31.7690   | 25.0986 |
| 0.1654        | 3.0902  | 2500  | 0.6037          | 32.8070   | 26.1459 |
| 0.172         | 3.7083  | 3000  | 0.5907          | 32.5790   | 25.2142 |
| 0.1214        | 4.3263  | 3500  | 0.6065          | 31.8337   | 24.9354 |
| 0.1488        | 4.9444  | 4000  | 0.6024          | 31.5376   | 24.9966 |
| 0.1034        | 5.5624  | 4500  | 0.6288          | 32.1161   | 25.4931 |
| 0.0818        | 6.1805  | 5000  | 0.6470          | 31.9051   | 25.5373 |
| 0.0955        | 6.7985  | 5500  | 0.6566          | 32.1195   | 25.4795 |
| 0.0744        | 7.4166  | 6000  | 0.6748          | 31.9153   | 25.6257 |
| 0.0784        | 8.0346  | 6500  | 0.6908          | 32.3577   | 25.9759 |
| 0.0684        | 8.6527  | 7000  | 0.6959          | 32.6538   | 26.3772 |
| 0.0587        | 9.2707  | 7500  | 0.7318          | 32.2931   | 25.7991 |
| 0.0656        | 9.8888  | 8000  | 0.7182          | 32.1467   | 25.8535 |
| 0.0589        | 10.5068 | 8500  | 0.7361          | 32.4428   | 26.3500 |
| 0.049         | 11.1248 | 9000  | 0.7597          | 32.3884   | 25.9827 |
| 0.0562        | 11.7429 | 9500  | 0.7504          | 32.2318   | 25.7481 |
| 0.0503        | 12.3609 | 10000 | 0.7422          | 32.1876   | 26.1493 |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0