deberta-large-ReqORNot – AI Model by kwang123 | AlphaNeural AI

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kwang123/
deberta-large-ReqORNot

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text-classification

generated_from_trainer

microsoft/deberta-v3-large

autotrain_compatible

endpoints_compatible

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deberta-large-ReqORNot

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

Loss: 0.5297
Accuracy: 0.9135
Weighted precision: 0.9135
Weighted recall: 0.9135
Weighted f1: 0.9134
Macro precision: 0.9135
Macro recall: 0.9128
Macro f1: 0.9131

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: 3
eval_batch_size: 3
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Weighted precision	Weighted recall	Weighted f1	Macro precision	Macro recall	Macro f1
0.4826	1.0	1896	0.4286	0.9020	0.9020	0.9020	0.9019	0.9018	0.9014	0.9016
0.3429	2.0	3792	0.4274	0.9077	0.9091	0.9077	0.9078	0.9076	0.9089	0.9076
0.1299	3.0	5688	0.5297	0.9135	0.9135	0.9135	0.9134	0.9135	0.9128	0.9131

Framework versions

Transformers 4.38.2
Pytorch 2.1.0+cu121
Datasets 2.18.0
Tokenizers 0.15.2