metadata
language:
- lus
license: apache-2.0
pipeline_tag: automatic-speech-recognition
base_model: Qwen/Qwen3-ASR-1.7B
tags:
- generated_from_trainer
datasets:
- andrewbawitlung/MiZonal-v3.0
metrics:
- wer
- cer
model-index:
- name: qwen3-asr-1.7b-mizonal3-E1-lus-v2026.06
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: MiZonal v3.0
type: andrewbawitlung/MiZonal-v3.0
config: default
split: test
metrics:
- name: Wer
type: wer
value: 24.0503
- name: Cer
type: cer
value: 5.2101
- name: Real Time Factor
type: rtf
value: 0.0596
qwen3-asr-1.7b-mizonal3-E1-lus-v2026.06
This model is a fine-tuned version of Qwen/Qwen3-ASR-1.7B on the MiZonal v3.0 dataset.
It achieves the following results on the evaluation set:
- Wer: 24.0503
- Cer: 5.2101
- Real Time Factor: 0.0596
Quick Inference
import torch
from qwen_asr import Qwen3ASRModel
# Load the model
model = Qwen3ASRModel.from_pretrained(
"andrewbawitlung/qwen3-asr-1.7b-mizonal3-E1-lus-v2026.06",
dtype=torch.bfloat16,
device_map="cuda:0" # Adjust device as needed
)
# Transcribe audio
results = model.transcribe("your_audio.wav")
print(results)
Model description
Experiment Configurations
This repository is part of a series of experiments. The different configurations are:
- E1 (Baseline): Standard training configuration.
- E2 (Noise): Training with background noise augmentation.
- E3 (Speed): Training with speed perturbation augmentation.
- E4 (SpecAug): Training with SpecAugment (time and frequency masking).
- E5 (Combined): Training with a combination of all augmentations.
All Models in this Family
| Experiment | Hugging Face Repository |
|---|---|
| E1 (Baseline) | andrewbawitlung/qwen3-asr-1.7b-mizonal3-E1-lus-v2026.06 |
| E2 (Noise) | andrewbawitlung/qwen3-asr-1.7b-mizonal3-E2-lus-v2026.06 |
| E3 (Speed) | andrewbawitlung/qwen3-asr-1.7b-mizonal3-E3-lus-v2026.06 |
| E4 (SpecAug) | andrewbawitlung/qwen3-asr-1.7b-mizonal3-E4-lus-v2026.06 |
| E5 (Combined) | andrewbawitlung/qwen3-asr-1.7b-mizonal3-E5-lus-v2026.06 |
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: OptimizerNames.ADAMW_TORCH_FUSED
- lr_scheduler_type: SchedulerType.LINEAR
- num_epochs: 8
Training results
| step | epoch | train_loss | eval_loss | eval_wer | eval_cer | learning_rate | grad_norm |
|---|---|---|---|---|---|---|---|
| 200 | 2.9018 | 0.4432 | 0.2900 | 24.8613 | 5.5626 | 1.31e-05 | 7.5000 |
| 400 | 5.8000 | 0.2058 | 0.2927 | 22.8374 | 5.2552 | 5.67e-06 | 6.2500 |