---
library_name: transformers
language:
- id
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- octava/InaVoCript-1.6
metrics:
- wer
model-index:
- name: ID Optimized Whisper Small for Inspirasi
  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. -->

# ID Optimized Whisper Small for Inspirasi

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Extracted Youtube with self developed dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3682
- Wer: 14.6104

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.0046        | 5.4054  | 1000 | 0.3295          | 14.9351 |
| 0.0004        | 10.8108 | 2000 | 0.3417          | 14.3506 |
| 0.0002        | 16.2162 | 3000 | 0.3556          | 14.7078 |
| 0.0002        | 21.6216 | 4000 | 0.3643          | 14.6753 |
| 0.0001        | 27.0270 | 5000 | 0.3682          | 14.6104 |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.2.0a0+81ea7a4
- Datasets 3.6.0
- Tokenizers 0.21.1