RoBERTa_token_classification_AraEval24_aug800 – AI Model by MM2157 | AlphaNeural AI

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MM2157/
RoBERTa_token_classification_AraEval24_aug800

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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RoBERTa_token_classification_AraEval24_aug800

This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.5882
Precision: 0.0607
Recall: 0.0717
F1: 0.0658
Accuracy: 0.6965

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.7043	1.0	1839	1.0921	0.0244	0.0115	0.0156	0.7401
0.4043	2.0	3678	1.1721	0.0428	0.0339	0.0378	0.7080
0.3146	3.0	5517	1.2162	0.0565	0.0583	0.0574	0.7032
0.2459	4.0	7356	1.3033	0.0641	0.0697	0.0668	0.7021
0.2155	5.0	9195	1.2839	0.0619	0.0523	0.0567	0.7322
0.1775	6.0	11034	1.3535	0.0653	0.0627	0.0640	0.7184
0.1598	7.0	12873	1.4153	0.0654	0.0702	0.0677	0.7092
0.1442	8.0	14712	1.5081	0.0636	0.0712	0.0672	0.6949
0.1287	9.0	16551	1.5040	0.0646	0.0687	0.0666	0.7068
0.108	10.0	18390	1.5882	0.0607	0.0717	0.0658	0.6965

Framework versions

Transformers 4.30.2
Pytorch 1.12.1
Datasets 2.13.2
Tokenizers 0.13.3