SPECTER-finetuned-DAGPap22 – AI Model by domenicrosati | AlphaNeural AI

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domenicrosati/
SPECTER-finetuned-DAGPap22

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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SPECTER-finetuned-DAGPap22

This model is a fine-tuned version of allenai/specter on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.0023
Accuracy: 0.9993
F1: 0.9995

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: 6e-06
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
num_epochs: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.3422	1.0	669	0.4135	0.8914	0.9140
0.1074	2.0	1338	0.1216	0.9746	0.9811
0.0329	3.0	2007	0.0064	0.9989	0.9992
0.0097	4.0	2676	0.0132	0.9972	0.9980
0.0123	5.0	3345	0.0231	0.9961	0.9971
0.0114	6.0	4014	0.0080	0.9985	0.9989
0.0029	7.0	4683	0.2207	0.9727	0.9797
0.0075	8.0	5352	0.0145	0.9974	0.9981
0.0098	9.0	6021	0.0047	0.9994	0.9996
0.0025	10.0	6690	0.0000	1.0	1.0
0.0044	11.0	7359	0.0035	0.9993	0.9995
0.0	12.0	8028	0.0027	0.9996	0.9997
0.0027	13.0	8697	0.0036	0.9993	0.9995
0.0055	14.0	9366	0.0017	0.9998	0.9999
0.0	15.0	10035	0.0000	1.0	1.0
0.0	16.0	10704	0.0000	1.0	1.0
0.0022	17.0	11373	0.0111	0.9981	0.9986
0.0004	18.0	12042	0.0011	0.9994	0.9996
0.0	19.0	12711	0.0020	0.9994	0.9996
0.0	20.0	13380	0.0023	0.9993	0.9995

Framework versions

Transformers 4.18.0
Pytorch 1.11.0
Datasets 2.1.0
Tokenizers 0.12.1