metadata
license: apache-2.0
base_model: arun100/whisper-base-th-1
tags:
- whisper-event
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Base Thai (2)
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: google/fleurs th_th
type: google/fleurs
config: th_th
split: test
args: th_th
metrics:
- name: Wer
type: wer
value: 53.662828506943114
Whisper Base Thai (2)
This model is a fine-tuned version of arun100/whisper-base-th-1 on the google/fleurs th_th dataset. It achieves the following results on the evaluation set:
- Loss: 0.5628
- Wer: 53.6628
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: 5e-07
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.5011 | 35.0 | 500 | 0.5963 | 59.8868 |
| 0.3648 | 71.0 | 1000 | 0.5613 | 55.9542 |
| 0.2732 | 107.0 | 1500 | 0.5504 | 54.4585 |
| 0.2081 | 142.0 | 2000 | 0.5502 | 53.6705 |
| 0.1627 | 178.0 | 2500 | 0.5558 | 53.8273 |
| 0.133 | 214.0 | 3000 | 0.5628 | 53.6628 |
| 0.1112 | 249.0 | 3500 | 0.5696 | 54.0798 |
| 0.0973 | 285.0 | 4000 | 0.5749 | 53.9995 |
| 0.0906 | 321.0 | 4500 | 0.5783 | 54.1487 |
| 0.0874 | 357.0 | 5000 | 0.5793 | 54.2290 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0