metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: whripser-small-thai
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_11_0
type: common_voice_11_0
config: th
split: test
args: th
metrics:
- name: Wer
type: wer
value: 90.98360655737704
whripser-small-thai
This model is a fine-tuned version of openai/whisper-small on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3703
- Wer: 90.9836
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-07
- 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4319 | 2.0 | 1000 | 0.4203 | 97.5410 |
| 0.4003 | 4.0 | 2000 | 0.3933 | 95.0820 |
| 0.3844 | 6.0 | 3000 | 0.3800 | 93.0328 |
| 0.3876 | 8.0 | 4000 | 0.3729 | 91.8033 |
| 0.3899 | 10.0 | 5000 | 0.3703 | 90.9836 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2