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---
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
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