bert-small-finetuned-xglue-ner-longer20

This model is a fine-tuned version of muhtasham/bert-small-finetuned-xglue-ner-longer10 on the wnut_17 dataset. It achieves the following results on the evaluation set:

• Loss: 0.5839
• Precision: 0.5783
• Recall: 0.4330
• F1: 0.4952
• Accuracy: 0.9261

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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	425	0.4882	0.5	0.4510	0.4742	0.9228
0.013	2.0	850	0.5039	0.5130	0.4246	0.4647	0.9242
0.0124	3.0	1275	0.5331	0.5506	0.4426	0.4907	0.9256
0.0159	4.0	1700	0.5403	0.5488	0.4234	0.4781	0.9249
0.0132	5.0	2125	0.5459	0.5714	0.4211	0.4848	0.9255
0.0117	6.0	2550	0.5522	0.5637	0.4342	0.4905	0.9253
0.0117	7.0	2975	0.5712	0.5778	0.4354	0.4966	0.9257
0.007	8.0	3400	0.5860	0.5828	0.4378	0.5	0.9259
0.0066	9.0	3825	0.5745	0.5703	0.4462	0.5007	0.9259
0.0049	10.0	4250	0.5839	0.5783	0.4330	0.4952	0.9261

Framework versions

• Transformers 4.21.1
• Pytorch 1.12.1+cu113
• Datasets 2.4.0
• Tokenizers 0.12.1