V11-bert-text-classification-model – AI Model by AmirlyPhd | AlphaNeural AI

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AmirlyPhd/
V11-bert-text-classification-model

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text-classification

generated_from_trainer

google-bert/bert-base-uncased

autotrain_compatible

endpoints_compatible

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V11-bert-text-classification-model

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: 0.4161
Accuracy: 0.8486
F1: 0.6847
Precision: 0.7825
Recall: 0.7045

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: 16
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 1
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
1.7046	0.11	50	1.7455	0.3120	0.1170	0.2748	0.1473
0.7733	0.22	100	0.6968	0.8069	0.4921	0.4803	0.5091
0.2603	0.33	150	0.5350	0.8903	0.6622	0.6451	0.6806
0.2477	0.44	200	0.4257	0.8841	0.6558	0.6363	0.6775
0.1487	0.55	250	0.3818	0.9150	0.6781	0.6632	0.6943
0.1528	0.66	300	0.3854	0.9048	0.6753	0.6694	0.6820
0.1611	0.76	350	0.2742	0.9169	0.6783	0.8038	0.6926
0.0925	0.87	400	0.2712	0.9155	0.6796	0.6665	0.6938
0.0954	0.98	450	0.3096	0.9119	0.6948	0.7995	0.7018

Framework versions

Transformers 4.39.3
Pytorch 2.1.2
Datasets 2.18.0
Tokenizers 0.15.2