metadata

language:
  - ko
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - fleurs
metrics:
  - wer
base_model: openai/whisper-small
model-index:
  - name: Whisper Small Ko(FLUERS) - by p4b
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: FLUERS Korean
          type: fleurs
          config: ko_kr
          split: validation
          args: ko_kr
        metrics:
          - type: wer
            value: 148.1005085252767
            name: Wer

Whisper Small Ko(FLUERS) - by p4b

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

Loss: 0.4512
Wer: 148.1005

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-07
train_batch_size: 96
eval_batch_size: 64
seed: 42
distributed_type: multi-GPU
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 500
training_steps: 4000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.6003	32.0	800	0.5913	167.2749
0.459	64.0	1600	0.4978	170.9841
0.4035	96.0	2400	0.4653	168.5911
0.3812	128.0	3200	0.4531	149.4765
0.3766	160.0	4000	0.4512	148.1005

Framework versions

Transformers 4.26.0.dev0
Pytorch 1.14.0.dev20221208+cu116
Datasets 2.7.1.dev0
Tokenizers 0.13.2