metadata
language:
- zh
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
base_model: openai/whisper-medium
model-index:
- name: Whisper medium nan-tw only char
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: mozilla-foundation/common_voice_11_0 nan-tw
type: mozilla-foundation/common_voice_11_0
config: nan-tw
split: test
args: nan-tw
metrics:
- type: wer
value: 45.2824427480916
name: Wer
Whisper medium nan-tw only char
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: 0.9944
- Wer: 45.2824
- Cer: 45.3667
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: 2
- eval_batch_size: 2
- 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 |
|---|---|---|---|---|---|
| 0.5832 | 1.04 | 1000 | 1.0634 | 56.3053 | 56.4745 |
| 0.1467 | 2.08 | 2000 | 1.0407 | 50.9618 | 51.0112 |
| 0.016 | 3.13 | 3000 | 1.0226 | 46.4427 | 46.5137 |
| 0.0001 | 5.01 | 4000 | 0.9974 | 45.4656 | 45.6082 |
| 0.0001 | 6.05 | 5000 | 0.9944 | 45.2824 | 45.3667 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2