metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: ywhisper-small-th
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: 13.228527607361965
ywhisper-small-th
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: 0.1841
- Wer: 13.2285
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: 0.0001
- 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 |
---|---|---|---|---|
0.0909 | 0.2 | 1000 | 0.3373 | 25.5752 |
0.0426 | 1.1 | 2000 | 0.2540 | 20.9739 |
0.0267 | 2.0 | 3000 | 0.2210 | 17.4080 |
0.0145 | 2.2 | 4000 | 0.2134 | 15.5675 |
0.0099 | 3.1 | 5000 | 0.1841 | 13.2285 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2