---
library_name: transformers
language:
- id
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- octava/indonesian-voice-transcription-1.4.9a-cv-fl-slrjv-md
model-index:
- name: Optimized Whisper Small Id 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. -->

# Optimized Whisper Small Id for Inspirasi

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Extracted Youtube with CommonVoice11, Fleurs, OpenSLR, and MagicData dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.3722
- eval_wer: 20.3324
- eval_runtime: 495.0068
- eval_samples_per_second: 3.527
- eval_steps_per_second: 0.222
- epoch: 3.0354
- step: 9000

## 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: 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: 10000
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.49.0
- Pytorch 2.2.0a0+81ea7a4
- Datasets 3.3.2
- Tokenizers 0.21.0