Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy	Adr Precision	Adr Recall	Adr F1	Drug Precision	Drug Recall	Drug F1	Finding Precision	Finding Recall	Finding F1	Symptom Precision	Symptom Recall	Symptom F1	B-adr Precision	B-adr Recall	B-adr F1	B-drug Precision	B-drug Recall	B-drug F1	B-finding Precision	B-finding Recall	B-finding F1	B-symptom Precision	B-symptom Recall	B-symptom F1	I-adr Precision	I-adr Recall	I-adr F1	I-drug Precision	I-drug Recall	I-drug F1	Macro Avg F1	Weighted Avg F1
No log	1.0	127	0.5842	0.3290	0.1573	0.2128	0.8274	0.1197	0.0624	0.0820	0.9293	0.5576	0.6970	0.0	0.0	0.0	0.0	0.0	0.0	0.4157	0.0710	0.1213	1.0	0.0667	0.125	0.0	0.0	0.0	0.0	0.0	0.0	0.0383	0.0203	0.0265	0.1212	0.0736	0.0916	0.0364	0.0764
No log	2.0	254	0.5137	0.2948	0.1910	0.2318	0.8476	0.1337	0.1028	0.1162	0.97	0.5879	0.7321	0.0	0.0	0.0	0.0	0.0	0.0	0.4724	0.2303	0.3097	0.9899	0.5939	0.7424	0.0	0.0	0.0	0.0	0.0	0.0	0.1053	0.0587	0.0754	0.97	0.5951	0.7376	0.1865	0.3023
No log	3.0	381	0.4805	0.3057	0.2022	0.2434	0.8500	0.1487	0.1138	0.1289	0.8850	0.6061	0.7194	0.0	0.0	0.0	0.0	0.0	0.0	0.5417	0.1747	0.2642	0.9623	0.6182	0.7528	0.0	0.0	0.0	0.0	0.0	0.0	0.0851	0.0632	0.0725	0.9252	0.6074	0.7333	0.1823	0.2858
0.5965	4.0	508	0.4963	0.3717	0.2260	0.2811	0.8570	0.2174	0.1468	0.1752	0.8487	0.6121	0.7113	0.0	0.0	0.0	0.0	0.0	0.0	0.5853	0.2438	0.3442	0.9630	0.6303	0.7619	0.0	0.0	0.0	0.0	0.0	0.0	0.1641	0.0948	0.1202	0.9107	0.6258	0.7418	0.1968	0.3312
0.5965	5.0	635	0.4448	0.3323	0.2759	0.3015	0.8619	0.2239	0.2165	0.2201	0.7574	0.6242	0.6844	0.0	0.0	0.0	0.0	0.0	0.0	0.5827	0.3109	0.4055	0.9561	0.6606	0.7814	0.0	0.0	0.0	0.0	0.0	0.0	0.1314	0.1219	0.1265	0.8031	0.6258	0.7034	0.2017	0.3531
0.5965	6.0	762	0.4285	0.3672	0.3021	0.3315	0.8682	0.2553	0.2440	0.2495	0.7970	0.6424	0.7114	0.0	0.0	0.0	0.6	0.1111	0.1875	0.6210	0.3743	0.4671	0.9569	0.6727	0.7900	0.0	0.0	0.0	0.6	0.12	0.2000	0.1641	0.1445	0.1537	0.8254	0.6380	0.7197	0.2330	0.3898
0.5965	7.0	889	0.4268	0.3582	0.3233	0.3399	0.8701	0.2531	0.2624	0.2577	0.7832	0.6788	0.7273	0.0	0.0	0.0	0.4444	0.1481	0.2222	0.5707	0.4338	0.4929	0.9268	0.6909	0.7917	0.0	0.0	0.0	0.5714	0.16	0.25	0.1932	0.1783	0.1854	0.7698	0.6564	0.7086	0.2429	0.4087
0.3701	8.0	1016	0.4297	0.3723	0.3221	0.3454	0.8725	0.2606	0.2606	0.2606	0.8175	0.6788	0.7417	0.0	0.0	0.0	0.5	0.1481	0.2286	0.5805	0.4223	0.4889	0.9370	0.7212	0.8151	0.0	0.0	0.0	0.5714	0.16	0.25	0.2020	0.1828	0.1919	0.8358	0.6871	0.7542	0.2500	0.4170
0.3701	9.0	1143	0.4345	0.3688	0.3333	0.3502	0.8717	0.2648	0.2716	0.2681	0.7958	0.6848	0.7362	0.3333	0.0222	0.0417	0.3571	0.1852	0.2439	0.5566	0.4530	0.4995	0.9023	0.7273	0.8054	1.0	0.0222	0.0435	0.4167	0.2	0.2703	0.2173	0.1874	0.2012	0.8235	0.6871	0.7492	0.2569	0.4237
0.3701	10.0	1270	0.4315	0.3648	0.3333	0.3483	0.8708	0.2667	0.2716	0.2691	0.7483	0.6848	0.7152	0.25	0.0222	0.0408	0.3333	0.1852	0.2381	0.5655	0.4472	0.4995	0.8768	0.7333	0.7987	1.0	0.0222	0.0435	0.4167	0.2	0.2703	0.2236	0.2009	0.2117	0.8	0.6871	0.7393	0.2563	0.4250

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0

mireiaplalis/distilbert-base-uncased-finetuned-ner-cadec

distilbert-base-uncased-finetuned-ner-cadec

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

mireiaplalis/
distilbert-base-uncased-finetuned-ner-cadec