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

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: 0.0139
- Wer: 7.6014

## 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     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.042         | 0.6410 | 250  | 0.0392          | 18.1869 |
| 0.023         | 1.2821 | 500  | 0.0318          | 14.5833 |
| 0.0158        | 1.9231 | 750  | 0.0215          | 10.5293 |
| 0.0106        | 2.5641 | 1000 | 0.0175          | 11.5428 |
| 0.0035        | 3.2051 | 1250 | 0.0145          | 7.5450  |
| 0.0027        | 3.8462 | 1500 | 0.0139          | 9.1779  |
| 0.0018        | 4.4872 | 1750 | 0.0144          | 7.5450  |
| 0.0016        | 5.1282 | 2000 | 0.0139          | 7.6014  |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.0
- Tokenizers 0.19.1