AraBERT_token_classification__AraEval24_fixed – AI Model by MM2157 | AlphaNeural AI

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MM2157/
AraBERT_token_classification__AraEval24_fixed

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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AraBERT_token_classification__AraEval24_fixed

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

Loss: 0.8758
Precision: 0.0901
Recall: 0.0234
F1: 0.0371
Accuracy: 0.8606

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
0.6563	1.0	2851	0.7705	0.0391	0.0006	0.0012	0.8632
0.5865	2.0	5702	0.8071	0.0909	0.0028	0.0055	0.8636
0.5382	3.0	8553	0.7815	0.0578	0.0012	0.0024	0.8634
0.5043	4.0	11404	0.7883	0.0798	0.0021	0.0041	0.8633
0.4445	5.0	14255	0.8188	0.0801	0.0031	0.0060	0.8637
0.4295	6.0	17106	0.8070	0.0877	0.0155	0.0263	0.8610
0.4096	7.0	19957	0.8184	0.0949	0.0135	0.0236	0.8627
0.3827	8.0	22808	0.8362	0.0818	0.0181	0.0296	0.8600
0.3525	9.0	25659	0.8458	0.0893	0.0254	0.0395	0.8599
0.3434	10.0	28510	0.8758	0.0901	0.0234	0.0371	0.8606

Framework versions

Transformers 4.30.2
Pytorch 1.12.1
Datasets 2.13.2
Tokenizers 0.13.3