metadata
language:
- ko
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- fleurs
metrics:
- wer
model-index:
- name: Whisper Small Ko(FLUERS) - by p4b
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: google/fleurs ko_kr
type: google/fleurs
config: ko_kr
split: test
metrics:
- name: Wer
type: wer
value: 20.251271313191744
Whisper Small Ko(FLUERS) - by p4b
This model is a fine-tuned version of openai/whisper-small on the FLUERS Korean dataset. It achieves the following results on the evaluation set:
- Loss: 0.2893
- Wer: 19.2
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
Dataset filtering
Some of datas from FLUERS are not used for training and evaluation. Most of filtered datas are not fit to model or including non-korean symbols.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-07
- train_batch_size: 96
- eval_batch_size: 64
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3016 | 32.0 | 800 | 0.4048 | 140.4726 |
| 0.0451 | 64.0 | 1600 | 0.2893 | 19.2043 |
| 0.0169 | 96.0 | 2400 | 0.3110 | 20.2513 |
| 0.0092 | 128.0 | 3200 | 0.3240 | 20.0419 |
| 0.0062 | 160.0 | 4000 | 0.3335 | 20.0419 |
| 0.0045 | 192.0 | 4800 | 0.3416 | 20.0718 |
| 0.0035 | 224.0 | 5600 | 0.3501 | 20.1615 |
| 0.0028 | 256.0 | 6400 | 0.3562 | 20.3709 |
| 0.0024 | 288.0 | 7200 | 0.3618 | 20.0120 |
| 0.002 | 320.0 | 8000 | 0.3669 | 20.1017 |
| 0.0017 | 352.0 | 8800 | 0.3704 | 20.1914 |
| 0.0017 | 384.0 | 9600 | 0.3723 | 20.2513 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.14.0.dev20221208+cu116
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2