finetune_whisper – AI Model by freshpearYoon | AlphaNeural AI

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freshpearYoon/
finetune_whisper

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automatic-speech-recognition

hf-asr-leaderboard

generated_from_trainer

openai/whisper-base

endpoints_compatible

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whisper_finetune

This model is a fine-tuned version of openai/whisper-base on the aihub_20000 dataset. It achieves the following results on the evaluation set:

Loss: 0.4938
Cer: 14.1359

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: 16
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
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Cer
0.3736	0.8	500	0.4641	15.1146
0.2685	1.6	1000	0.4525	14.3150
0.1929	2.4	1500	0.4424	14.0470
0.1241	3.2	2000	0.4584	13.8724
0.1347	4.0	2500	0.4554	13.9110
0.0944	4.8	3000	0.4693	14.0391
0.0761	5.6	3500	0.4851	14.1281
0.0606	6.4	4000	0.4938	14.1359

Framework versions

Transformers 4.37.0.dev0
Pytorch 1.12.1+cu113
Datasets 2.15.0
Tokenizers 0.15.0