---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- fleurs
metrics:
- wer
model-index:
- name: whisper-small-shona
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: fleurs
      type: fleurs
      config: sn_zw
      split: test
      args: sn_zw
    metrics:
    - name: Wer
      type: wer
      value: 50.04219409282701
---

<!-- 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-shona

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1298
- Wer: 50.0422

## 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: 8
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- gradient_accumulation_steps: 2
- total_train_batch_size: 48
- total_eval_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.0064        | 24.24  | 400  | 0.9630          | 50.7233 |
| 0.001         | 48.48  | 800  | 1.0617          | 49.9397 |
| 0.0005        | 72.73  | 1200 | 1.1016          | 49.9397 |
| 0.0004        | 96.97  | 1600 | 1.1220          | 49.9096 |
| 0.0003        | 121.21 | 2000 | 1.1298          | 50.0422 |


### Framework versions

- Transformers 4.37.1
- Pytorch 1.12.0+cu102
- Datasets 2.16.1
- Tokenizers 0.15.1