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---
library_name: transformers
language:
- id
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- octava/extracted-id-subbed-video-v2
metrics:
- wer
model-index:
- name: Whisper Small Id - Inspirasi
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Extracted id video v2
type: octava/extracted-id-subbed-video-v2
config: id
split: test
args: 'config: id, split: test'
metrics:
- name: Wer
type: wer
value: 28.173403414112286
---
<!-- 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. -->
# Whisper Small Id - Inspirasi
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Extracted id video v2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4480
- Wer: 28.1734
## 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 |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.2601 | 0.5615 | 1000 | 0.3923 | 29.8060 |
| 0.1176 | 1.1230 | 2000 | 0.3954 | 30.3875 |
| 0.0848 | 1.6844 | 3000 | 0.4068 | 29.2758 |
| 0.0317 | 2.2459 | 4000 | 0.4088 | 26.8850 |
| 0.0261 | 2.8074 | 5000 | 0.4480 | 28.1734 |
### Framework versions
- Transformers 4.49.0
- Pytorch 2.2.0a0+81ea7a4
- Datasets 3.3.2
- Tokenizers 0.21.0
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