fine-tuned-bert-base-uncased – AI Model by TheKnight115 | AlphaNeural AI

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TheKnight115/
fine-tuned-bert-base-uncased

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text-classification

generated_from_trainer

google-bert/bert-base-uncased

autotrain_compatible

endpoints_compatible

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fine-tuned-bert-base-uncased

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

Loss: 0.2400
F1: 0.7987
Roc Auc: 0.8779
Accuracy: 0.5990

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: 2e-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
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.2624	1.0	2002	0.2666	0.6748	0.7869	0.4353
0.2129	2.0	4004	0.2405	0.7226	0.8141	0.4914
0.1541	3.0	6006	0.2436	0.7561	0.8450	0.5380
0.1197	4.0	8008	0.2352	0.7887	0.8704	0.5795
0.0897	5.0	10010	0.2400	0.7987	0.8779	0.5990

Framework versions

Transformers 4.38.2
Pytorch 2.1.2
Datasets 2.1.0
Tokenizers 0.15.2