deberta-v3-base4scientific-claim-verification – AI Model by nicolauduran45 | AlphaNeural AI

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nicolauduran45/
deberta-v3-base4scientific-claim-verification

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text-classification

generated_from_trainer

microsoft/deberta-v3-base

autotrain_compatible

endpoints_compatible

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classifier

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

Loss: 0.9760
F1-micro: 0.7354
F1-macro: 0.7202
F1-weighted: 0.7314
Accuracy: 0.7354

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: 16
eval_batch_size: 8
seed: 42
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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	F1-micro	F1-macro	F1-weighted	Accuracy
No log	1.0	386	0.7548	0.6615	0.6527	0.6627	0.6615
0.8384	2.0	772	0.6518	0.7134	0.6981	0.7073	0.7134
0.6001	3.0	1158	0.6752	0.7419	0.7313	0.7408	0.7419
0.3926	4.0	1544	0.7489	0.7354	0.7232	0.7304	0.7354
0.3926	5.0	1930	0.9760	0.7354	0.7202	0.7314	0.7354

Framework versions

Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.1