Model3_Marabertv2_T2_WOS – AI Model by SMG0 | AlphaNeural AI

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SMG0/
Model3_Marabertv2_T2_WOS

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text-classification

generated_from_trainer

UBC-NLP/MARBERTv2

autotrain_compatible

endpoints_compatible

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Model3_Marabertv2_T2_WOS

This model is a fine-tuned version of UBC-NLP/MARBERTv2 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0816
F1: 0.8297
Roc Auc: 0.9146
Accuracy: 0.7412

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: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
No log	1.0	193	0.1523	0.5204	0.6899	0.3743
No log	2.0	386	0.1084	0.7070	0.7979	0.5940
0.162	3.0	579	0.0896	0.7799	0.8517	0.6872
0.162	4.0	772	0.0814	0.8089	0.8834	0.7281
0.162	5.0	965	0.0845	0.8037	0.8866	0.7244
0.0569	6.0	1158	0.0814	0.8112	0.8968	0.7095
0.0569	7.0	1351	0.0744	0.8253	0.9009	0.7225
0.0258	8.0	1544	0.0754	0.8313	0.9081	0.7207
0.0258	9.0	1737	0.0754	0.8418	0.9171	0.7579
0.0258	10.0	1930	0.0813	0.8264	0.9143	0.7356
0.0145	11.0	2123	0.0816	0.8297	0.9146	0.7412

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3