---
language:
- ymr
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: leenag/Norm_KLuke_Med
  results: []
---

<!-- 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. -->

# leenag/Norm_KLuke_Med

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Spoken Bible Corpus: Malasar dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5144
- Wer: 44.9541

## 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: 16
- 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: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.0275        | 11.3636 | 250  | 0.3935          | 48.5092 |
| 0.0091        | 22.7273 | 500  | 0.4626          | 49.0252 |
| 0.0012        | 34.0909 | 750  | 0.4798          | 47.1330 |
| 0.0002        | 45.4545 | 1000 | 0.5015          | 46.3876 |
| 0.0001        | 56.8182 | 1250 | 0.4947          | 45.5849 |
| 0.0           | 68.1818 | 1500 | 0.5088          | 45.0688 |
| 0.0           | 79.5455 | 1750 | 0.5129          | 44.9541 |
| 0.0           | 90.9091 | 2000 | 0.5144          | 44.9541 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.0.1+cu117
- Datasets 2.16.0
- Tokenizers 0.19.1