roberta-ner – AI Model by devanshrj | AlphaNeural AI

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devanshrj/
roberta-ner

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token-classification

generated_from_trainer

FacebookAI/roberta-base

autotrain_compatible

endpoints_compatible

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roberta-ner

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

Loss: 0.1963
Precision: 0.3814
Recall: 0.4134
F1: 0.3968
Accuracy: 0.9525

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: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	60	0.2553	0.1878	0.1075	0.1368	0.9435
No log	2.0	120	0.2114	0.3456	0.2235	0.2714	0.9492
No log	3.0	180	0.2007	0.3372	0.3673	0.3516	0.9494
No log	4.0	240	0.1976	0.3618	0.3911	0.3758	0.9517
No log	5.0	300	0.1963	0.3814	0.4134	0.3968	0.9525

Framework versions

Transformers 4.34.1
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1