train3 – AI Model by freshpearYoon | AlphaNeural AI

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freshpearYoon/
train3

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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_3 dataset. It achieves the following results on the evaluation set:

Loss: 0.3587
Cer: 11.8692
Wer: 34.6801

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	Cer	Validation Loss	Wer
0.267	0.4	500	11.9783	0.3521	35.1998
0.2392	0.8	1000	12.1614	0.3495	34.9449
0.171	1.2	1500	12.0633	0.3516	35.2048
0.1744	1.6	2000	0.3553	12.2091	35.0598
0.1722	2.0	2500	0.3515	12.0222	34.5426
0.1192	2.4	3000	0.3594	12.2281	35.4796
0.1249	2.8	3500	0.3609	12.0137	34.8949
0.0858	3.2	4000	0.3587	11.8692	34.6801

Framework versions

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