metadata
language:
- zh
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- cer-char
- cer-rome
model-index:
- name: Whisper medium nan-tw
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_11_0 nan-tw
type: mozilla-foundation/common_voice_11_0
config: nan-tw
split: train
args: nan-tw
metrics:
- name: Cer-char
type: cer
value: 45.038167938931295
- name: Cer-rome
type: cer
value: 31.56572704437622
Whisper medium nan-tw
This model is a fine-tuned version of openai/whisper-medium on the mozilla-foundation/common_voice_11_0 nan-tw dataset. It achieves the following results on the evaluation set:
- Loss: 0.9100
- Wer: 42.0709
- Cer: 22.3681
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: 8
- eval_batch_size: 8
- 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 | Cer |
|---|---|---|---|---|---|
| 0.0568 | 5.0 | 1000 | 0.7769 | 48.2706 | 26.0890 |
| 0.0057 | 10.0 | 2000 | 0.8438 | 44.0722 | 23.9270 |
| 0.0041 | 15.01 | 3000 | 0.8740 | 42.8540 | 22.9554 |
| 0.0001 | 20.01 | 4000 | 0.9041 | 42.1797 | 22.5496 |
| 0.0001 | 25.01 | 5000 | 0.9100 | 42.0709 | 22.3681 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2