whisper-base-finetuned-common_voice – AI Model by aydink | AlphaNeural AI

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aydink/
whisper-base-finetuned-common_voice

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audio-classification

generated_from_trainer

openai/whisper-base

endpoints_compatible

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whisper-base-finetuned-common_voice

This model is a fine-tuned version of openai/whisper-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0001
Accuracy: 1.0
F1: 1.0
Recall: 1.0
Precision: 1.0
Mcc: 1.0
Auc: 1.0

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: 8
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_ratio: 0.1
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Recall	Precision	Mcc	Auc
0.0012	1.0	200	0.0024	1.0	1.0	1.0	1.0	1.0	1.0
0.0874	2.0	400	0.1391	0.975	0.9748	0.975	0.9773	0.9694	1.0
0.0003	3.0	600	0.0003	1.0	1.0	1.0	1.0	1.0	1.0
0.0002	4.0	800	0.0002	1.0	1.0	1.0	1.0	1.0	1.0
0.0001	5.0	1000	0.0002	1.0	1.0	1.0	1.0	1.0	1.0
0.0001	6.0	1200	0.0001	1.0	1.0	1.0	1.0	1.0	1.0
0.0001	7.0	1400	0.0001	1.0	1.0	1.0	1.0	1.0	1.0
0.0001	8.0	1600	0.0001	1.0	1.0	1.0	1.0	1.0	1.0
0.0001	9.0	1800	0.0001	1.0	1.0	1.0	1.0	1.0	1.0
0.0001	10.0	2000	0.0001	1.0	1.0	1.0	1.0	1.0	1.0

Framework versions

Transformers 4.41.0
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1