entailed_after_rte-bert-base-uncased – AI Model by kennethge123 | AlphaNeural AI

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kennethge123/
entailed_after_rte-bert-base-uncased

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text-classification

generated_from_trainer

kennethge123/superglue_rte-bert-base-uncased

autotrain_compatible

endpoints_compatible

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entailed_after_rte-bert-base-uncased

This model is a fine-tuned version of kennethge123/superglue_rte-bert-base-uncased on the bigbench dataset. It achieves the following results on the evaluation set:

Loss: 0.7322
Accuracy: 0.5714

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: 4
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	30	0.6876	0.5714
No log	2.0	60	0.8029	0.5714
No log	3.0	90	0.7246	0.5714
No log	4.0	120	0.7152	0.5714
No log	5.0	150	0.7887	0.5714
No log	6.0	180	0.7498	0.5714
No log	7.0	210	0.8149	0.4286
No log	8.0	240	0.7055	0.5714
No log	9.0	270	0.7209	0.5714
No log	10.0	300	0.6922	0.5714
No log	11.0	330	0.7186	0.5714
No log	12.0	360	0.6916	0.5714
No log	13.0	390	0.7233	0.5714
No log	14.0	420	0.7109	0.5714
No log	15.0	450	0.7051	0.5714
No log	16.0	480	0.6968	0.5714
0.7046	17.0	510	0.7068	0.5714
0.7046	18.0	540	0.7319	0.5714
0.7046	19.0	570	0.7301	0.5714
0.7046	20.0	600	0.7322	0.5714

Framework versions

Transformers 4.37.0
Pytorch 1.13.1+cu117
Datasets 2.15.0
Tokenizers 0.15.2