bert-finetuned-sem_eval-english – AI Model by rlreichel | AlphaNeural AI

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rlreichel/
bert-finetuned-sem_eval-english

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text-classification

generated_from_trainer

google-bert/bert-base-uncased

autotrain_compatible

endpoints_compatible

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bert-finetuned-sem_eval-english

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: 0.1822
F1: 0.7501
Roc Auc: 0.8476
Accuracy: 0.3329

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: 50
eval_batch_size: 50
seed: 42
distributed_type: tpu
optimizer: Use OptimizerNames.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	F1	Roc Auc	Accuracy
0.3222	1.0	849	0.2118	0.6913	0.8003	0.2515
0.191	2.0	1698	0.1867	0.7190	0.8126	0.2944
0.1583	3.0	2547	0.1827	0.7477	0.8479	0.3231
0.1422	4.0	3396	0.1803	0.7474	0.8420	0.3302
0.127	5.0	4245	0.1822	0.7501	0.8476	0.3329

Framework versions

Transformers 4.48.3
Pytorch 2.5.1+cpu
Datasets 3.3.2
Tokenizers 0.21.0