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alionder/acer_nitro_mdberta

sourceHugging Facemitupdated 3y agoView on Hugging Face

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acernitromdberta

This model is a fine-tuned version of microsoft/mdeberta-v3-base on the None dataset. It achieves the following results on the evaluation set:

—Loss: 0.7384
—F1: 0.7593
—Roc Auc: 0.8588
—Accuracy: 0.6506

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
—trainbatchsize: 2
—evalbatchsize: 2
—seed: 42
—optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
—lrschedulertype: linear
—num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
No log	1.0	166	0.5907	0.7281	0.8497	0.5904
No log	2.0	332	0.5260	0.6836	0.8576	0.5181
No log	3.0	498	0.7023	0.7324	0.8381	0.6024
0.3153	4.0	664	0.7848	0.7245	0.8168	0.5904
0.3153	5.0	830	0.6979	0.7436	0.8666	0.5904
0.3153	6.0	996	0.8550	0.7426	0.8337	0.6265
0.1464	7.0	1162	0.7102	0.7830	0.8700	0.6747
0.1464	8.0	1328	0.7172	0.7721	0.8662	0.6627
0.1464	9.0	1494	0.7812	0.7664	0.8613	0.6506
0.0781	10.0	1660	0.7384	0.7593	0.8588	0.6506

Framework versions

—Transformers 4.36.2
—Pytorch 2.1.0+cu121
—Datasets 2.16.1
—Tokenizers 0.15.0