|
--- |
|
language: |
|
- ja |
|
license: other |
|
tags: |
|
- whisper-event |
|
- generated_from_trainer |
|
datasets: |
|
- Elite35P-Server/EliteVoiceProject |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Whisper Base Japanese Elite |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: Elite35P-Server/EliteVoiceProject twitter |
|
type: Elite35P-Server/EliteVoiceProject |
|
config: twitter |
|
split: test |
|
args: twitter |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 17.073170731707318 |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# Whisper Base Japanese Elite |
|
|
|
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Elite35P-Server/EliteVoiceProject twitter dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4385 |
|
- Wer: 17.0732 |
|
|
|
## 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: 32 |
|
- eval_batch_size: 32 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: constant_with_warmup |
|
- lr_scheduler_warmup_steps: 200 |
|
- training_steps: 10000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:------:|:-----:|:---------------:|:-------:| |
|
| 0.0002 | 111.0 | 1000 | 0.2155 | 9.7561 | |
|
| 0.0001 | 222.0 | 2000 | 0.2448 | 12.1951 | |
|
| 0.0 | 333.0 | 3000 | 0.2674 | 13.4146 | |
|
| 0.0 | 444.0 | 4000 | 0.2943 | 15.8537 | |
|
| 0.0 | 555.0 | 5000 | 0.3182 | 17.0732 | |
|
| 0.0 | 666.0 | 6000 | 0.3501 | 18.9024 | |
|
| 0.0 | 777.0 | 7000 | 0.3732 | 16.4634 | |
|
| 0.0 | 888.0 | 8000 | 0.4025 | 17.0732 | |
|
| 0.0 | 999.0 | 9000 | 0.4178 | 20.1220 | |
|
| 0.0 | 1111.0 | 10000 | 0.4385 | 17.0732 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.26.0.dev0 |
|
- Pytorch 1.13.1+cu117 |
|
- Datasets 2.8.1.dev0 |
|
- Tokenizers 0.13.2 |
|
|
