ennedendahakotubert – AI Model by OsBaran | AlphaNeural AI

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OsBaran/
ennedendahakotubert

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text-classification

generated_from_trainer

google-bert/bert-base-uncased

autotrain_compatible

endpoints_compatible

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ennedendahakotubert

This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.6561
Accuracy: 0.5476
F1: 0.4969
Precision: 0.5597
Recall: 0.4468

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
gradient_accumulation_steps: 4
total_train_batch_size: 64
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
lr_scheduler_warmup_steps: 500
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
2.5202	1.0	771	0.6304	0.5729	0.3810	0.6921	0.2628
2.52	2.0	1542	0.6230	0.5768	0.6437	0.5559	0.7644
2.399	3.0	2313	0.6289	0.5682	0.6491	0.5467	0.7988
2.4829	4.0	3084	0.6366	0.5552	0.6149	0.5422	0.7101
2.4135	5.0	3855	0.6561	0.5476	0.4969	0.5597	0.4468

Framework versions

Transformers 4.47.1
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0