ner-fine-tune-roberta-new

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

• Loss: 0.3320
• Precision: 0.2696
• Recall: 0.3767
• F1: 0.3143
• Accuracy: 0.9389

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: 1e-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: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	122	0.2264	0.0	0.0	0.0	0.9542
No log	2.0	244	0.1874	0.2348	0.1349	0.1713	0.9571
No log	3.0	366	0.1739	0.2420	0.2279	0.2347	0.9528
No log	4.0	488	0.1656	0.1939	0.2233	0.2076	0.9472
0.2548	5.0	610	0.1740	0.3243	0.2767	0.2986	0.9573
0.2548	6.0	732	0.2087	0.2562	0.2628	0.2595	0.9464
0.2548	7.0	854	0.1921	0.2773	0.2953	0.2860	0.9495
0.2548	8.0	976	0.2038	0.2602	0.3860	0.3109	0.9397
0.0748	9.0	1098	0.2324	0.2371	0.3093	0.2684	0.9398
0.0748	10.0	1220	0.2329	0.2852	0.3442	0.3119	0.9436
0.0748	11.0	1342	0.2670	0.2521	0.3535	0.2943	0.9356
0.0748	12.0	1464	0.2607	0.2509	0.3186	0.2807	0.9395
0.033	13.0	1586	0.2645	0.2655	0.3791	0.3123	0.9359
0.033	14.0	1708	0.2947	0.2838	0.4442	0.3463	0.9398
0.033	15.0	1830	0.2807	0.2945	0.3349	0.3134	0.9451
0.033	16.0	1952	0.2990	0.2910	0.3302	0.3094	0.9448
0.0181	17.0	2074	0.2915	0.2799	0.3651	0.3169	0.9425
0.0181	18.0	2196	0.2853	0.2868	0.3535	0.3167	0.9424
0.0181	19.0	2318	0.2991	0.2918	0.3814	0.3306	0.9440
0.0181	20.0	2440	0.2863	0.2762	0.3744	0.3179	0.9408
0.0111	21.0	2562	0.3280	0.2796	0.3628	0.3158	0.9409
0.0111	22.0	2684	0.3135	0.2772	0.3372	0.3043	0.9431
0.0111	23.0	2806	0.3282	0.2632	0.3698	0.3075	0.9404
0.0111	24.0	2928	0.3306	0.2597	0.3884	0.3113	0.9369
0.0078	25.0	3050	0.3135	0.2743	0.3605	0.3116	0.9414
0.0078	26.0	3172	0.3320	0.2646	0.3791	0.3117	0.9374
0.0078	27.0	3294	0.3273	0.2659	0.3791	0.3126	0.9381
0.0078	28.0	3416	0.3290	0.2616	0.3674	0.3056	0.9380
0.0055	29.0	3538	0.3366	0.2656	0.3860	0.3147	0.9372
0.0055	30.0	3660	0.3320	0.2696	0.3767	0.3143	0.9389

Framework versions

• Transformers 4.34.1
• Pytorch 2.1.0+cu118
• Datasets 2.14.6
• Tokenizers 0.14.1