---
language:
- sn
license: apache-2.0
library_name: peft
tags:
- whisper-event and peft-lora
- generated_from_trainer
base_model: openai/whisper-tiny
datasets:
- Kittech/kittech_shona_dataset
metrics:
- wer
model-index:
- name: Whisper Small Sn - Bright Chirindo
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: Kingdom Truth International Ministries sermons
      type: Kittech/kittech_shona_dataset
      config: sn_zw
      split: test
      args: sn_zw
    metrics:
    - type: wer
      value: 208.88577256501785
      name: Wer
---

<!-- 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 Sn - Bright Chirindo

This model is a fine-tuned version of [kittech/whisper-tiny-sn](https://huggingface.co/kittech/whisper-tiny-sn) on the Kingdom Truth International Ministries sermons dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9243
- Wer: 208.8858

## 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: 8
- 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: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step | Validation Loss | Wer      |
|:-------------:|:--------:|:----:|:---------------:|:--------:|
| 2.5155        | 357.1429 | 2500 | 2.9250          | 212.4044 |
| 2.1292        | 714.2857 | 5000 | 2.9243          | 208.8858 |


### Framework versions

- PEFT 0.10.1.dev0
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.2.dev0
- Tokenizers 0.19.1