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