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

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NainaSuraj/
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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This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.3223
F1: 0.8380
Roc Auc: 0.8801
Accuracy: 0.5157

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: 0.0001
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.3549	1.0	584	0.3053	0.7922	0.8376	0.4682
0.2657	2.0	1168	0.2684	0.8279	0.8678	0.5087
0.2232	3.0	1752	0.2917	0.8330	0.8740	0.5093
0.1695	4.0	2336	0.2991	0.8349	0.8774	0.5145
0.1215	5.0	2920	0.3223	0.8380	0.8801	0.5157

Framework versions

Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2