---
library_name: transformers
language:
- multilingual
license: apache-2.0
base_model: openai/whisper-tiny.en
tags:
- generated_from_trainer
datasets:
- edutjie/bisix_su_id
metrics:
- wer
model-index:
- name: 'BisiX: Sundanese Whisper'
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: SU ID ASR
      type: edutjie/bisix_su_id
      config: su_id_asr_source
      split: validation
      args: su_id_asr_source
    metrics:
    - name: Wer
      type: wer
      value: 33.87865168539326
---

<!-- 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. -->

# BisiX: Sundanese Whisper

This model is a fine-tuned version of [openai/whisper-tiny.en](https://huggingface.co/openai/whisper-tiny.en) on the SU ID ASR dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0180
- Wer: 33.8787
- Cer: 11.6897

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 30
- training_steps: 150
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     | Cer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|
| 4.3455        | 0.1765 | 30   | 2.4772          | 85.1326 | 33.9863 |
| 1.7093        | 0.3529 | 60   | 1.3486          | 41.4562 | 15.2167 |
| 1.2183        | 0.5294 | 90   | 1.1469          | 36.2247 | 12.5208 |
| 1.0676        | 0.7059 | 120  | 1.0517          | 34.6427 | 11.9084 |
| 0.9974        | 0.8824 | 150  | 1.0180          | 33.8787 | 11.6897 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1