metadata
language:
- lus
license: apache-2.0
pipeline_tag: automatic-speech-recognition
base_model: openai/whisper-medium
tags:
- audio
- automatic-speech-recognition
datasets:
- andrewbawitlung/MiZonal-v2.0
metrics:
- wer
model-index:
- name: Whisper Medium
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: MiZonal v2.0
type: andrewbawitlung/MiZonal-v2.0
config: default
split: train
args: 'config: lus, split: test'
metrics:
- name: Wer
type: wer
value: 15.345099014002816
Whisper Medium
This model is a fine-tuned version of openai/whisper-medium on the MiZonal v2.0.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2789
- Wer: 15.3451
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 6000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4096 | 0.66 | 500 | 0.3767 | 28.0139 |
| 0.1929 | 1.31 | 1000 | 0.2698 | 20.9877 |
| 0.1757 | 1.97 | 1500 | 0.2310 | 19.7199 |
| 0.089 | 2.62 | 2000 | 0.2347 | 19.1234 |
| 0.0405 | 3.28 | 2500 | 0.2445 | 18.8334 |
| 0.0423 | 3.93 | 3000 | 0.2450 | 17.3585 |
| 0.0188 | 4.59 | 3500 | 0.2535 | 18.1622 |
| 0.0077 | 5.24 | 4000 | 0.2613 | 16.8862 |
| 0.0074 | 5.9 | 4500 | 0.2661 | 16.1240 |
| 0.0027 | 6.55 | 5000 | 0.2710 | 15.3865 |
| 0.001 | 7.21 | 5500 | 0.2763 | 15.3948 |
| 0.001 | 7.86 | 6000 | 0.2789 | 15.3451 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.3.1+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1