---
language:
- ymr
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: leenag/Malasar_Medium
  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_Medium

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Spoken Bible Corpus: Malasar dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5907
- Wer: 50.2570

## 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     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.0646        | 11.3636 | 250  | 0.3369          | 55.6254 |
| 0.0104        | 22.7273 | 500  | 0.4445          | 52.3130 |
| 0.0012        | 34.0909 | 750  | 0.4890          | 50.1428 |
| 0.0002        | 45.4545 | 1000 | 0.5240          | 50.3712 |
| 0.0002        | 56.8182 | 1250 | 0.5488          | 50.1999 |
| 0.0001        | 68.1818 | 1500 | 0.5695          | 50.3712 |
| 0.0001        | 79.5455 | 1750 | 0.5844          | 50.1999 |
| 0.0001        | 90.9091 | 2000 | 0.5907          | 50.2570 |


### Framework versions

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