v12_bert-base-uncased-finetuned-mrpc – AI Model by VitaliiVrublevskyi | AlphaNeural AI

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VitaliiVrublevskyi/
v12_bert-base-uncased-finetuned-mrpc

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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v12_bert-base-uncased-finetuned-mrpc

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: 1.7151
Accuracy: 0.7623
F1: 0.8418

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: 32
eval_batch_size: 32
seed: 63
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	Accuracy	F1
0.4064	1.0	719	0.6134	0.8015	0.8643
0.1426	2.0	1438	1.2114	0.7696	0.8479
0.0209	3.0	2157	1.4115	0.7819	0.8514
0.0136	4.0	2876	1.5548	0.7672	0.8403
0.0041	5.0	3595	1.7151	0.7623	0.8418

Framework versions

Transformers 4.28.0
Pytorch 2.1.0+cu118
Datasets 2.14.7
Tokenizers 0.13.3