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BRlkl/
BingoGuard-bert-base-custom-only

Name: BingoGuard-bert-base-custom-only
Availability: InStock

generated_from_trainer

neuralmind/bert-base-portuguese-cased

finetune

mit

text-embeddings-inference

endpoints_compatible

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BingoGuard-bert-base-custom-only

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

Loss: 0.6610
Accuracy: 0.8766
F1: 0.8745

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: 5e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.381	1.0	67	0.2833	0.9	0.8920
0.2434	2.0	134	0.3236	0.8979	0.8943
0.1175	3.0	201	0.4126	0.8702	0.8737
0.06	4.0	268	0.6708	0.8426	0.852
0.0495	5.0	335	0.5486	0.8766	0.8728
0.0187	6.0	402	0.6512	0.8787	0.8779
0.0072	7.0	469	0.6511	0.8745	0.8709
0.0375	8.0	536	0.6610	0.8766	0.8745

Framework versions

Transformers 4.55.4
Pytorch 2.8.0+cu128
Datasets 3.6.0
Tokenizers 0.21.4

BRlkl/BingoGuard-bert-base-custom-only

BingoGuard-bert-base-custom-only

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

BRlkl/
BingoGuard-bert-base-custom-only