fabert_keyphrase – AI Model by hesamheidari | AlphaNeural AI

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hesamheidari/
fabert_keyphrase

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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fabert_keyphrase

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

Loss: 0.1864
Precision: 0.4945
Recall: 0.5211
F1: 0.5074
Accuracy: 0.9384

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: 16
eval_batch_size: 16
seed: 42
optimizer: Use 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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.1368	1.0	2107	0.1610	0.4900	0.4727	0.4812	0.9407
0.1227	2.0	4214	0.1620	0.5066	0.4962	0.5014	0.9415
0.108	3.0	6321	0.1659	0.5072	0.5109	0.5090	0.9407
0.0943	4.0	8428	0.1749	0.4996	0.5083	0.5039	0.9391
0.0845	5.0	10535	0.1864	0.4945	0.5211	0.5074	0.9384

Framework versions

Transformers 4.55.4
Pytorch 2.6.0+cu126
Datasets 3.4.0
Tokenizers 0.21.1