fine-tune-bert-combined – AI Model by nouman-10 | AlphaNeural AI

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nouman-10/
fine-tune-bert-combined

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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fine-tune-bert-combined

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

Loss: 2.4606
Accuracy: 0.7326
F1: 0.6954

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: 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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.444	1.0	1819	0.6302	0.6948	0.6182
0.3182	2.0	3638	0.6042	0.7703	0.7508
0.2082	3.0	5457	0.9061	0.7064	0.6505
0.1301	4.0	7276	1.1842	0.7413	0.7262
0.0883	5.0	9095	1.6491	0.7529	0.7267
0.0564	6.0	10914	2.1418	0.7093	0.6429
0.0385	7.0	12733	2.0313	0.7384	0.7134
0.0156	8.0	14552	2.2918	0.7413	0.7245
0.0108	9.0	16371	2.3513	0.7413	0.7101
0.0131	10.0	18190	2.4606	0.7326	0.6954

Framework versions

Transformers 4.26.1
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2