roberta

This model is a fine-tuned version of Jean-Baptiste/roberta-large-ner-english on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.3908
• Precision: 0.5990
• Recall: 0.5581
• F1: 0.5778
• Accuracy: 0.9470

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: 0.0001
• train_batch_size: 32
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.99) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	151	0.2078	0.1899	0.2388	0.2115	0.9246
No log	2.0	302	0.1499	0.4322	0.5535	0.4854	0.9393
No log	3.0	453	0.1916	0.5204	0.4946	0.5072	0.9418
0.1542	4.0	604	0.1671	0.4615	0.5109	0.4849	0.9426
0.1542	5.0	755	0.1940	0.4841	0.4829	0.4835	0.9439
0.1542	6.0	906	0.2462	0.5066	0.5651	0.5343	0.9428
0.0616	7.0	1057	0.2106	0.5041	0.5271	0.5153	0.9437
0.0616	8.0	1208	0.2621	0.5620	0.5202	0.5403	0.9474
0.0616	9.0	1359	0.2903	0.5242	0.5550	0.5392	0.9440
0.0326	10.0	1510	0.3083	0.5883	0.5628	0.5753	0.9483
0.0326	11.0	1661	0.3125	0.5451	0.5853	0.5645	0.9444
0.0326	12.0	1812	0.3616	0.5503	0.5388	0.5445	0.9427
0.0326	13.0	1963	0.3398	0.5978	0.5023	0.5459	0.9447
0.0155	14.0	2114	0.2942	0.5701	0.5550	0.5625	0.9467
0.0155	15.0	2265	0.3723	0.5771	0.5597	0.5683	0.9462
0.0155	16.0	2416	0.3651	0.5751	0.5760	0.5755	0.9439
0.0062	17.0	2567	0.3674	0.5667	0.5891	0.5777	0.9455
0.0062	18.0	2718	0.3866	0.5897	0.5403	0.5639	0.9463
0.0062	19.0	2869	0.3908	0.5990	0.5581	0.5778	0.9470
0.0033	20.0	3020	0.4036	0.5914	0.5620	0.5763	0.9467

Framework versions

• Transformers 4.31.0
• Pytorch 2.0.1+cu117
• Datasets 2.14.2
• Tokenizers 0.13.3