bert-base-uncased-finetuned-rte-run_trial2 – AI Model by BoranIsmet | AlphaNeural AI

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BoranIsmet/
bert-base-uncased-finetuned-rte-run_trial2

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text-classification

generated_from_trainer

google-bert/bert-base-uncased

autotrain_compatible

endpoints_compatible

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bert-base-uncased-finetuned-rte-run_trial2

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: 0.6427
Accuracy: 0.6606

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: 128
eval_batch_size: 128
seed: 42
optimizer: Use OptimizerNames.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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	20	0.6768	0.5740
No log	2.0	40	0.6574	0.6318
No log	3.0	60	0.6427	0.6606
No log	4.0	80	0.6405	0.6426
No log	5.0	100	0.6501	0.6498
No log	6.0	120	0.6685	0.6570
No log	7.0	140	0.6927	0.6245
No log	8.0	160	0.7180	0.6426
No log	9.0	180	0.7300	0.6390
No log	10.0	200	0.7346	0.6534

Framework versions

Transformers 4.50.3
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1