metadata
language:
- th
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
- lotus
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Small Thai 7k
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_11_0 th
type: mozilla-foundation/common_voice_11_0
config: th
split: test
args: th
metrics:
- name: Wer
type: wer
value: 14.69
Whisper Tiny Thai
This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_11_0, lotus, google/fleurs th,None,th_th dataset. It achieves the following results on the evaluation set:
- Loss: 0.2262
- Wer: 14.69
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: 64
- eval_batch_size: 32
- 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: 7000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0473 | 0.14 | 1000 | 0.2459 | 21.6283 |
| 0.0253 | 1.07 | 2000 | 0.1970 | 17.2157 |
| 0.0181 | 2.0 | 3000 | 0.2017 | 17.8993 |
| 0.0088 | 2.15 | 4000 | 0.2148 | 16.8428 |
| 0.0055 | 3.07 | 5000 | 0.2166 | 15.8484 |
| 0.0048 | 4.0 | 6000 | 0.2261 | 16.0348 |
| 0.0026 | 4.15 | 7000 | 0.2262 | 15.5998 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2