metadata
language:
- ko
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- slplab/asd_apac
metrics:
- wer
pipeline_tag: automatic-speech-recognition
duplicated_from: slplab/whisper-large_v2-asd_v1
base_model: openai/whisper-large-v2
model-index:
- name: whisper-large_v2-asd_v1
results: []
whisper-large_v2-asd_v1
This model is a fine-tuned version of openai/whisper-large-v2 on slplab/asd_apac dataset. It achieves the following results on the validation set:
- Loss: 0.8553
- Wer: 78.4722
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: 32
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0617 | 10.53 | 100 | 0.6858 | 81.9444 |
| 0.004 | 21.05 | 200 | 0.7322 | 79.8611 |
| 0.0005 | 31.58 | 300 | 0.7923 | 80.5556 |
| 0.0003 | 42.11 | 400 | 0.8131 | 79.1667 |
| 0.0002 | 52.63 | 500 | 0.8263 | 76.7361 |
| 0.0002 | 63.16 | 600 | 0.8365 | 77.4306 |
| 0.0002 | 73.68 | 700 | 0.8451 | 78.4722 |
| 0.0002 | 84.21 | 800 | 0.8503 | 78.4722 |
| 0.0002 | 94.74 | 900 | 0.8541 | 78.4722 |
| 0.0002 | 105.26 | 1000 | 0.8553 | 78.4722 |
Test results
- Loss: 0.6359
- Wer: 36.6876
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3