---
library_name: transformers
language:
- multilingual
license: apache-2.0
base_model: openai/whisper-tiny.en
tags:
- generated_from_trainer
datasets:
- arkanalexei/bisix_su_id_reset
metrics:
- wer
model-index:
- name: 'BisiX: Sundanese Whisper (Reset Params)'
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: SU ID ASR
      type: arkanalexei/bisix_su_id_reset
      config: su_id_asr_source
      split: validation
      args: su_id_asr_source
    metrics:
    - name: Wer
      type: wer
      value: 100.0
---

<!-- 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 (Reset Params)

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: 10.8462
- Wer: 100.0
- Cer: 100.0

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- 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       |
|:-------------:|:------:|:----:|:---------------:|:---------:|:---------:|
| 10.856        | 0.3529 | 30   | 10.8546         | 1611.8562 | 2230.5547 |
| 10.853        | 0.7059 | 60   | 10.8517         | 100.0     | 83.0372   |
| 10.8498       | 1.0588 | 90   | 10.8486         | 100.0     | 95.0543   |
| 10.8475       | 1.4118 | 120  | 10.8467         | 100.0     | 100.0     |
| 10.8463       | 1.7647 | 150  | 10.8462         | 100.0     | 100.0     |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.1+cu124
- Datasets 3.0.1
- Tokenizers 0.20.0