metadata

license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: Japanese_Fine_Tuned_Whisper_Model
    results: []
datasets:
  - mozilla-foundation/common_voice_11_0
language:
  - ja

Japanese_Fine_Tuned_Whisper_Model

This model is a fine-tuned version of openai/whisper-tiny on the Common Voice dataset. It achieves the following results on the evaluation set:

Loss: 0.549100
Wer: 225.233037

Model description

The tiny Whisper model is fine-tuned on Japanese speech samples from the Common Voice dataset, based on which users can perform Automatic Speech Recognition in real time in Japanese.

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: 100
training_steps: 1000
mixed_precision_training: Native AMP

Training results

Training Loss	Step	Validation Loss	Wer
0.8097	200	0.801917	601.560806
0.7200	400	0.783436	327.335790
0.6810	600	0.759281	254.064600
0.7351	800	0.747759	241.426404
0.5491	1000	0.747127	225.233037

Framework versions

Transformers 4.27.0.dev0
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2