deberta-v3-large-ad-opentag-finetuned-ner-2epochs

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: 0.0023
• Precision: 0.9843
• Recall: 0.9911
• F1: 0.9877
• Accuracy: 0.9996

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0041	1.0	8909	0.0036	0.9746	0.9838	0.9792	0.9993
0.0032	2.0	17818	0.0023	0.9843	0.9911	0.9877	0.9996

Framework versions

• Transformers 4.30.1
• Pytorch 2.0.1+cu117
• Datasets 2.12.0
• Tokenizers 0.13.3