BERT_headline_classifier_v2 – AI Model by harshil0217 | AlphaNeural AI

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harshil0217/
BERT_headline_classifier_v2

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google-bert/bert-base-cased

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bert-base-cased

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

Loss: 0.4598
Accuracy: 0.8648
Precision: 0.8676
Recall: 0.8679
F1: 0.8677

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
No log	1.0	243	0.2591	0.8421	0.8563	0.8545	0.8534
No log	2.0	486	0.2780	0.8277	0.8388	0.8328	0.8315
0.2582	3.0	729	0.3394	0.8524	0.8545	0.8555	0.8550
0.2582	4.0	972	0.3391	0.8545	0.8631	0.8596	0.8612
0.0768	5.0	1215	0.3966	0.8617	0.8632	0.8638	0.8631
0.0768	6.0	1458	0.4443	0.8627	0.8660	0.8658	0.8654
0.0228	7.0	1701	0.4502	0.8648	0.8683	0.8648	0.8665
0.0228	8.0	1944	0.4598	0.8648	0.8676	0.8679	0.8677

Framework versions

Transformers 4.42.4
Pytorch 2.3.1+cu121
Tokenizers 0.19.1