nguyenkhoa2407/favs_token_classification_v2_updated_data

来源：🤗有风险🏴‍☠️ 救援者：isilicontoken-classificationapache-2.0432 MBother✓ 2 个校验和1,459 天前更新

favs_token_classification_v2_updated_data

This model is a fine-tuned version of bert-base-cased on the token_classification_v2 dataset. It achieves the following results on the evaluation set:

Loss: 0.5346
Precision: 0.6923
Recall: 0.8357
F1: 0.7573
Accuracy: 0.8493

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: 1.5e-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: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
2.3096	1.0	13	1.9927	0.3011	0.2	0.2403	0.3726
2.038	2.0	26	1.7093	0.2569	0.2643	0.2606	0.4274
1.8391	3.0	39	1.4452	0.3057	0.4214	0.3544	0.5562
1.4912	4.0	52	1.2176	0.4130	0.5429	0.4691	0.6493
1.3296	5.0	65	1.0368	0.4973	0.6643	0.5688	0.7123
1.2036	6.0	78	0.9084	0.5053	0.6786	0.5793	0.7260
0.9244	7.0	91	0.8148	0.5543	0.7286	0.6296	0.7616
0.8293	8.0	104	0.7482	0.5698	0.7286	0.6395	0.7726
0.7422	9.0	117	0.6961	0.5833	0.75	0.6562	0.7836
0.6379	10.0	130	0.6613	0.6124	0.7786	0.6855	0.8027
0.6071	11.0	143	0.6357	0.6193	0.7786	0.6899	0.8082
0.5526	12.0	156	0.6033	0.6433	0.7857	0.7074	0.8164
0.537	13.0	169	0.5813	0.6512	0.8	0.7179	0.8301
0.4806	14.0	182	0.5706	0.6608	0.8071	0.7267	0.8329
0.4503	15.0	195	0.5594	0.6647	0.8071	0.7290	0.8356
0.4149	16.0	208	0.5503	0.6805	0.8214	0.7443	0.8438
0.4175	17.0	221	0.5430	0.6824	0.8286	0.7484	0.8438
0.4337	18.0	234	0.5396	0.6923	0.8357	0.7573	0.8493
0.3965	19.0	247	0.5361	0.6882	0.8357	0.7548	0.8493
0.3822	20.0	260	0.5346	0.6923	0.8357	0.7573	0.8493

Framework versions

Transformers 4.21.1
Pytorch 1.12.1
Datasets 2.4.0
Tokenizers 0.12.1