metadata

language:
  - vi
license: apache-2.0
base_model: openai/whisper-base
tags:
  - generated_from_trainer
datasets:
  - vivos
metrics:
  - wer
model-index:
  - name: Whisper Base Vi - Duy Ta
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Vivos
          type: vivos
          config: clean vivos
          split: None
        metrics:
          - name: Wer
            type: wer
            value: 25.058275058275058

Whisper Base Vi - DuyTa

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

Loss: 0.2565
Wer: 25.0583

Model description

Finetune Whisper model on Vietnamese Dataset

Intended uses & limitations

More information needed

Training and evaluation data

Vivos

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 1e-05
train_batch_size: 16
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: 4000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2096	1.37	1000	0.2949	32.0383
0.1205	2.74	2000	0.2548	26.8583
0.0767	4.12	3000	0.2549	25.3432
0.0532	5.49	4000	0.2565	25.0583

Framework versions

Transformers 4.31.0.dev0
Pytorch 2.0.1+cu117
Datasets 2.13.1
Tokenizers 0.13.3