bert_base_km_5_v2_mrpc – AI Model by Hartunka | AlphaNeural AI

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Hartunka/
bert_base_km_5_v2_mrpc

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text-classification

generated_from_trainer

Hartunka/bert_base_km_5_v2

autotrain_compatible

endpoints_compatible

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bert_base_km_5_v2_mrpc

This model is a fine-tuned version of Hartunka/bert_base_km_5_v2 on the GLUE MRPC dataset. It achieves the following results on the evaluation set:

Loss: 0.5978
Accuracy: 0.7157
F1: 0.8054
Combined Score: 0.7605

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: 256
eval_batch_size: 256
seed: 10
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Combined Score
0.6316	1.0	15	0.6041	0.6887	0.7961	0.7424
0.5501	2.0	30	0.5978	0.7157	0.8054	0.7605
0.4475	3.0	45	0.6495	0.6642	0.7617	0.7130
0.3135	4.0	60	0.8099	0.6716	0.7682	0.7199
0.1742	5.0	75	1.1510	0.5882	0.6719	0.6301
0.0858	6.0	90	1.1825	0.6275	0.7196	0.6735
0.0492	7.0	105	1.3777	0.6642	0.7720	0.7181

Framework versions

Transformers 4.50.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.21.1