results – AI Model by kaizoku56 | AlphaNeural AI

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text-classification

generated_from_trainer

google-bert/bert-base-uncased

autotrain_compatible

endpoints_compatible

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results

This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.1065
Accuracy: 0.9764

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: 5e-05
train_batch_size: 64
eval_batch_size: 40
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 10
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1363	0.4	500	0.0833	0.9706
0.0839	0.8	1000	0.0788	0.9725
0.0608	1.19	1500	0.1042	0.9750
0.0449	1.59	2000	0.0826	0.9751
0.0436	1.99	2500	0.0760	0.9765
0.0187	2.39	3000	0.1041	0.9765
0.0156	2.78	3500	0.1065	0.9764

Framework versions

Transformers 4.39.3
Pytorch 2.1.2
Datasets 2.18.0
Tokenizers 0.15.2