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anhphuong/
whisper_largev2_jp

Name: whisper_largev2_jp
Availability: InStock

automatic-speech-recognition

generated_from_trainer

google/fleurs

model-index

endpoints_compatible

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Whisper Large V2 Ja - Anh Phuong

This model is a fine-tuned version of openai/whisper-largev2-ja-v2 on the Google fleurs dataset. It achieves the following results on the evaluation set:

Loss: 0.2626
Wer: 58.2472

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: 16
eval_batch_size: 4
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: 6000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.004	6.25	1000	0.2030	61.0044
0.0022	12.5	2000	0.2081	60.6105
0.0002	18.75	3000	0.2401	58.7888
0.0001	25.0	4000	0.2531	58.6411
0.0001	31.25	5000	0.2598	58.2472
0.0001	37.5	6000	0.2626	58.2472

Framework versions

Transformers 4.42.3
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1

anhphuong/whisper_largev2_jp

Whisper Large V2 Ja - Anh Phuong

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

anhphuong/
whisper_largev2_jp