metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: openai/whisper-tiny
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_11_0
type: common_voice_11_0
config: zh-TW
split: test
args: zh-TW
metrics:
- name: Wer
type: wer
value: 72.79426816786079
openai/whisper-tiny
This model is a fine-tuned version of openai/whisper-tiny on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6159
- Wer: 72.7943
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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1257 | 6.02 | 1000 | 0.4811 | 69.3552 |
| 0.0122 | 13.02 | 2000 | 0.5494 | 70.6858 |
| 0.0044 | 20.01 | 3000 | 0.5851 | 71.3818 |
| 0.0028 | 27.0 | 4000 | 0.6098 | 72.6919 |
| 0.0022 | 33.02 | 5000 | 0.6159 | 72.7943 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2