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---
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
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