bert-base-cased-finetuned-ner-cadec

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

Loss: 0.5960
Precision: 0.6145
Recall: 0.6931
F1: 0.6514
Accuracy: 0.9158
Adr Precision: 0.5972
Adr Recall: 0.7167
Adr F1: 0.6515
Disease Precision: 0.1613
Disease Recall: 0.2
Disease F1: 0.1786
Drug Precision: 0.9042
Drug Recall: 0.9321
Drug F1: 0.9179
Finding Precision: 0.375
Finding Recall: 0.2174
Finding F1: 0.2752
Symptom Precision: 0.2895
Symptom Recall: 0.4074
Symptom F1: 0.3385
B-adr Precision: 0.7488
B-adr Recall: 0.8177
B-adr F1: 0.7817
B-disease Precision: 0.2083
B-disease Recall: 0.2
B-disease F1: 0.2041
B-drug Precision: 0.9512
B-drug Recall: 0.9630
B-drug F1: 0.9571
B-finding Precision: 0.5882
B-finding Recall: 0.3030
B-finding F1: 0.4000
B-symptom Precision: 0.5769
B-symptom Recall: 0.5556
B-symptom F1: 0.5660
I-adr Precision: 0.5822
I-adr Recall: 0.694
I-adr F1: 0.6332
I-disease Precision: 0.1667
I-disease Recall: 0.2083
I-disease F1: 0.1852
I-drug Precision: 0.9096
I-drug Recall: 0.9321
I-drug F1: 0.9207
I-finding Precision: 0.4194
I-finding Recall: 0.2281
I-finding F1: 0.2955
I-symptom Precision: 0.16
I-symptom Recall: 0.3077
I-symptom F1: 0.2105
Macro Avg F1: 0.5154
Weighted Avg F1: 0.7079

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: 40

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy	Adr Precision	Adr Recall	Adr F1	Disease Precision	Disease Recall	Disease 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-disease Precision	B-disease Recall	B-disease 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-disease Precision	I-disease Recall	I-disease F1	I-drug Precision	I-drug Recall	I-drug F1	I-finding Precision	I-finding Recall	I-finding F1	I-symptom Precision	I-symptom Recall	I-symptom F1	Macro Avg F1	Weighted Avg F1
No log	1.0	125	0.3119	0.4995	0.6195	0.5531	0.8982	0.4482	0.6567	0.5328	0.0968	0.12	0.1071	0.8108	0.9259	0.8646	0.0	0.0	0.0	0.0	0.0	0.0	0.6662	0.7947	0.7248	0.5	0.04	0.0741	0.8966	0.9630	0.9286	0.0	0.0	0.0	0.0	0.0	0.0	0.4471	0.634	0.5244	0.0645	0.0833	0.0727	0.8389	0.9321	0.8830	0.0	0.0	0.0	0.0	0.0	0.0	0.3208	0.6051
No log	2.0	250	0.2753	0.5678	0.6591	0.6101	0.9080	0.5287	0.6917	0.5993	0.1667	0.28	0.2090	0.8895	0.9444	0.9162	0.2174	0.0725	0.1087	0.6667	0.0741	0.1333	0.7216	0.7982	0.7580	0.3333	0.28	0.3043	0.9290	0.9691	0.9486	0.5	0.1212	0.1951	0.6667	0.0741	0.1333	0.5211	0.668	0.5855	0.2105	0.3333	0.2581	0.8947	0.9444	0.9189	0.3571	0.0877	0.1408	0.0	0.0	0.0	0.4243	0.6632
No log	3.0	375	0.2933	0.5759	0.6659	0.6176	0.9068	0.5568	0.6867	0.6149	0.1273	0.28	0.175	0.8629	0.9321	0.8961	0.2955	0.1884	0.2301	0.7143	0.1852	0.2941	0.7267	0.7858	0.7551	0.1795	0.28	0.2188	0.9181	0.9691	0.9429	0.7407	0.3030	0.4301	0.8571	0.2222	0.3529	0.5486	0.666	0.6016	0.16	0.3333	0.2162	0.8889	0.9383	0.9129	0.4333	0.2281	0.2989	0.0	0.0	0.0	0.4729	0.6831
0.2637	4.0	500	0.3117	0.5807	0.6602	0.6179	0.9105	0.5554	0.6683	0.6067	0.1304	0.24	0.1690	0.8686	0.9383	0.9021	0.3265	0.2319	0.2712	0.6667	0.2963	0.4103	0.7310	0.7982	0.7631	0.2188	0.28	0.2456	0.9181	0.9691	0.9429	0.6774	0.3182	0.4330	0.8889	0.2963	0.4444	0.5517	0.64	0.5926	0.1795	0.2917	0.2222	0.8786	0.9383	0.9075	0.4324	0.2807	0.3404	0.3333	0.0769	0.125	0.5017	0.6873
0.2637	5.0	625	0.3290	0.5881	0.6693	0.6261	0.9114	0.5636	0.6867	0.6191	0.1579	0.24	0.1905	0.8802	0.9074	0.8936	0.2857	0.2029	0.2373	0.6	0.4444	0.5106	0.7192	0.8071	0.7606	0.28	0.28	0.28	0.9509	0.9568	0.9538	0.6562	0.3182	0.4286	0.8	0.4444	0.5714	0.5583	0.67	0.6091	0.2414	0.2917	0.2642	0.9130	0.9074	0.9102	0.3333	0.2456	0.2828	0.8571	0.4615	0.6	0.5661	0.6978
0.2637	6.0	750	0.3484	0.5547	0.6489	0.5981	0.9061	0.5310	0.6417	0.5811	0.1765	0.36	0.2368	0.8994	0.9383	0.9184	0.3243	0.1739	0.2264	0.2941	0.5556	0.3846	0.7249	0.7929	0.7574	0.2093	0.36	0.2647	0.9398	0.9630	0.9512	0.6667	0.2121	0.3218	0.6296	0.6296	0.6296	0.5391	0.634	0.5827	0.1739	0.3333	0.2286	0.9042	0.9321	0.9179	0.3667	0.1930	0.2529	0.1842	0.5385	0.2745	0.5181	0.6811
0.2637	7.0	875	0.3724	0.5410	0.6727	0.5997	0.9065	0.5164	0.6833	0.5882	0.1714	0.24	0.2000	0.8655	0.9136	0.8889	0.3269	0.2464	0.2810	0.2826	0.4815	0.3562	0.6933	0.8442	0.7614	0.25	0.24	0.2449	0.9277	0.9506	0.9390	0.6286	0.3333	0.4356	0.6667	0.5926	0.6275	0.5329	0.664	0.5913	0.2333	0.2917	0.2593	0.8810	0.9136	0.8970	0.375	0.2632	0.3093	0.1818	0.4615	0.2609	0.5326	0.6885
0.0793	8.0	1000	0.3738	0.6018	0.6727	0.6353	0.9135	0.5743	0.6633	0.6156	0.25	0.2	0.2222	0.8869	0.9198	0.9030	0.3699	0.3913	0.3803	0.4545	0.5556	0.5	0.7492	0.7823	0.7654	0.2778	0.2	0.2326	0.9448	0.9506	0.9477	0.58	0.4394	0.5	0.625	0.5556	0.5882	0.5671	0.642	0.6023	0.3571	0.2083	0.2632	0.9085	0.9198	0.9141	0.4179	0.4912	0.4516	0.2778	0.3846	0.3226	0.5588	0.7034
0.0793	9.0	1125	0.4368	0.5911	0.6614	0.6243	0.9077	0.5673	0.6533	0.6073	0.1667	0.32	0.2192	0.8779	0.9321	0.9042	0.3659	0.2174	0.2727	0.5	0.6667	0.5714	0.7441	0.7770	0.7602	0.2143	0.36	0.2687	0.9235	0.9691	0.9458	0.64	0.2424	0.3516	0.68	0.6296	0.6538	0.5622	0.624	0.5915	0.1707	0.2917	0.2154	0.9096	0.9321	0.9207	0.4167	0.2632	0.3226	0.3043	0.5385	0.3889	0.5419	0.6894
0.0793	10.0	1250	0.4367	0.5972	0.6784	0.6352	0.9113	0.5623	0.6917	0.6203	0.2258	0.28	0.25	0.9207	0.9321	0.9264	0.3421	0.1884	0.2430	0.4062	0.4815	0.4407	0.7171	0.8301	0.7695	0.28	0.28	0.28	0.9509	0.9568	0.9538	0.6333	0.2879	0.3958	0.8235	0.5185	0.6364	0.5717	0.678	0.6203	0.2143	0.25	0.2308	0.9146	0.9259	0.9202	0.4074	0.1930	0.2619	0.25	0.3846	0.3030	0.5372	0.7016
0.0793	11.0	1375	0.4405	0.5978	0.6784	0.6355	0.9118	0.5663	0.6833	0.6193	0.1714	0.24	0.2000	0.9036	0.9259	0.9146	0.4286	0.2609	0.3243	0.4286	0.5556	0.4839	0.7254	0.7947	0.7584	0.2308	0.24	0.2353	0.9625	0.9506	0.9565	0.5938	0.2879	0.3878	0.6429	0.6667	0.6545	0.5714	0.672	0.6176	0.1613	0.2083	0.1818	0.9091	0.9259	0.9174	0.4706	0.2807	0.3516	0.25	0.3846	0.3030	0.5364	0.6986
0.0302	12.0	1500	0.4536	0.6151	0.6716	0.6421	0.9154	0.5859	0.6767	0.6280	0.2	0.2	0.2000	0.9036	0.9259	0.9146	0.4074	0.3188	0.3577	0.3846	0.3704	0.3774	0.7442	0.7982	0.7703	0.2632	0.2	0.2273	0.9627	0.9568	0.9598	0.5952	0.3788	0.4630	0.75	0.4444	0.5581	0.5742	0.658	0.6132	0.2174	0.2083	0.2128	0.9146	0.9259	0.9202	0.4565	0.3684	0.4078	0.1875	0.2308	0.2069	0.5339	0.7050
0.0302	13.0	1625	0.4545	0.6216	0.6920	0.6549	0.9147	0.5886	0.7033	0.6409	0.2222	0.24	0.2308	0.9325	0.9383	0.9354	0.4091	0.2609	0.3186	0.4062	0.4815	0.4407	0.7492	0.8035	0.7754	0.24	0.24	0.24	0.975	0.9630	0.9689	0.5897	0.3485	0.4381	0.6667	0.5185	0.5833	0.5762	0.688	0.6272	0.2083	0.2083	0.2083	0.9325	0.9383	0.9354	0.5152	0.2982	0.3778	0.2857	0.4615	0.3529	0.5507	0.7133
0.0302	14.0	1750	0.4876	0.5982	0.6761	0.6348	0.9136	0.5718	0.69	0.6254	0.1515	0.2	0.1724	0.8988	0.9321	0.9152	0.3636	0.2319	0.2832	0.3793	0.4074	0.3929	0.7291	0.8195	0.7717	0.2	0.2	0.2000	0.9455	0.9630	0.9541	0.5882	0.3030	0.4000	0.75	0.5556	0.6383	0.5676	0.672	0.6154	0.1613	0.2083	0.1818	0.9042	0.9321	0.9179	0.4167	0.2632	0.3226	0.1765	0.2308	0.2000	0.5202	0.7002
0.0302	15.0	1875	0.5015	0.5958	0.6795	0.6349	0.9118	0.5592	0.685	0.6157	0.2	0.2	0.2000	0.8830	0.9321	0.9069	0.4255	0.2899	0.3448	0.4483	0.4815	0.4643	0.7252	0.8265	0.7725	0.2381	0.2	0.2174	0.9286	0.9630	0.9455	0.6154	0.3636	0.4571	0.7143	0.5556	0.6250	0.5466	0.668	0.6013	0.2083	0.2083	0.2083	0.8988	0.9321	0.9152	0.4474	0.2982	0.3579	0.2778	0.3846	0.3226	0.5423	0.6999
0.0138	16.0	2000	0.5115	0.6038	0.6784	0.6389	0.9122	0.5836	0.6867	0.6309	0.2188	0.28	0.2456	0.9096	0.9321	0.9207	0.4048	0.2464	0.3063	0.2609	0.4444	0.3288	0.7517	0.8035	0.7767	0.25	0.28	0.2642	0.9568	0.9568	0.9568	0.5405	0.3030	0.3883	0.5517	0.5926	0.5714	0.5673	0.666	0.6127	0.2069	0.25	0.2264	0.9036	0.9259	0.9146	0.5	0.2982	0.3736	0.1379	0.3077	0.1905	0.5275	0.7028
0.0138	17.0	2125	0.5120	0.6181	0.6874	0.6509	0.9161	0.5810	0.6933	0.6322	0.1852	0.2	0.1923	0.8994	0.9383	0.9184	0.5385	0.3043	0.3889	0.4194	0.4815	0.4483	0.7335	0.8088	0.7694	0.2083	0.2	0.2041	0.9398	0.9630	0.9512	0.6667	0.3333	0.4444	0.7273	0.5926	0.6531	0.5799	0.668	0.6208	0.1923	0.2083	0.2	0.9157	0.9383	0.9268	0.6364	0.3684	0.4667	0.25	0.3077	0.2759	0.5512	0.7098
0.0138	18.0	2250	0.5226	0.6088	0.6874	0.6457	0.9140	0.5679	0.6967	0.6257	0.2	0.2	0.2000	0.8935	0.9321	0.9124	0.5882	0.2899	0.3883	0.3939	0.4815	0.4333	0.7233	0.8142	0.7660	0.2381	0.2	0.2174	0.9455	0.9630	0.9541	0.6774	0.3182	0.4330	0.6667	0.5926	0.6275	0.5552	0.674	0.6089	0.2174	0.2083	0.2128	0.9042	0.9321	0.9179	0.6071	0.2982	0.4	0.2381	0.3846	0.2941	0.5432	0.7016
0.0138	19.0	2375	0.5139	0.6151	0.6806	0.6462	0.9148	0.5862	0.6917	0.6346	0.1923	0.2	0.1961	0.8935	0.9321	0.9124	0.4419	0.2754	0.3393	0.3548	0.4074	0.3793	0.7463	0.8018	0.7730	0.2381	0.2	0.2174	0.9398	0.9630	0.9512	0.6216	0.3485	0.4466	0.6364	0.5185	0.5714	0.5697	0.67	0.6158	0.2083	0.2083	0.2083	0.9152	0.9321	0.9235	0.5	0.2982	0.3736	0.2	0.3077	0.2424	0.5323	0.7047
0.0087	20.0	2500	0.5420	0.5994	0.6795	0.6369	0.9129	0.5646	0.6917	0.6217	0.2083	0.2	0.2041	0.8882	0.9321	0.9096	0.4615	0.2609	0.3333	0.3333	0.4074	0.3667	0.7167	0.8106	0.7608	0.25	0.2	0.2222	0.9398	0.9630	0.9512	0.6	0.3182	0.4158	0.7143	0.5556	0.6250	0.5572	0.682	0.6133	0.2174	0.2083	0.2128	0.9042	0.9321	0.9179	0.5	0.2632	0.3448	0.2273	0.3846	0.2857	0.5350	0.6981
0.0087	21.0	2625	0.5395	0.6113	0.6840	0.6456	0.9121	0.5773	0.6967	0.6314	0.1786	0.2	0.1887	0.9207	0.9321	0.9264	0.4857	0.2464	0.3269	0.3514	0.4815	0.4062	0.7237	0.8159	0.7671	0.2083	0.2	0.2041	0.9627	0.9568	0.9598	0.6333	0.2879	0.3958	0.6154	0.5926	0.6038	0.5675	0.664	0.6120	0.2	0.2083	0.2041	0.9264	0.9321	0.9292	0.5926	0.2807	0.3810	0.24	0.4615	0.3158	0.5373	0.7018
0.0087	22.0	2750	0.5431	0.6174	0.6908	0.6521	0.9158	0.5868	0.71	0.6425	0.1724	0.2	0.1852	0.9036	0.9259	0.9146	0.4706	0.2319	0.3107	0.3939	0.4815	0.4333	0.7391	0.8071	0.7716	0.2273	0.2	0.2128	0.9571	0.9630	0.9600	0.625	0.3030	0.4082	0.6154	0.5926	0.6038	0.5712	0.69	0.6250	0.1923	0.2083	0.2	0.9146	0.9259	0.9202	0.5	0.2281	0.3133	0.2273	0.3846	0.2857	0.5300	0.7045
0.0087	23.0	2875	0.5375	0.6111	0.7010	0.6530	0.9168	0.5741	0.7167	0.6375	0.1667	0.16	0.1633	0.9207	0.9321	0.9264	0.4348	0.2899	0.3478	0.4667	0.5185	0.4912	0.7182	0.8301	0.7701	0.25	0.2	0.2222	0.9627	0.9568	0.9598	0.6216	0.3485	0.4466	0.6957	0.5926	0.6400	0.5731	0.69	0.6261	0.2105	0.1667	0.1860	0.9146	0.9259	0.9202	0.5	0.3158	0.3871	0.2632	0.3846	0.3125	0.5471	0.7093
0.0049	24.0	3000	0.5681	0.6144	0.6965	0.6529	0.9134	0.5905	0.7233	0.6502	0.1724	0.2	0.1852	0.8935	0.9321	0.9124	0.3438	0.1594	0.2178	0.3889	0.5185	0.4444	0.7254	0.8230	0.7711	0.2174	0.2	0.2083	0.9451	0.9568	0.9509	0.6296	0.2576	0.3656	0.6538	0.6296	0.6415	0.5802	0.702	0.6353	0.1786	0.2083	0.1923	0.9096	0.9321	0.9207	0.4348	0.1754	0.2500	0.24	0.4615	0.3158	0.5252	0.7034
0.0049	25.0	3125	0.5550	0.6216	0.7089	0.6624	0.9169	0.5954	0.7283	0.6552	0.1724	0.2	0.1852	0.9259	0.9259	0.9259	0.4524	0.2754	0.3423	0.375	0.5556	0.4478	0.7362	0.8248	0.7780	0.2273	0.2	0.2128	0.9688	0.9568	0.9627	0.6216	0.3485	0.4466	0.6	0.6667	0.6316	0.5867	0.704	0.6400	0.1923	0.2083	0.2	0.9259	0.9259	0.9259	0.5	0.2807	0.3596	0.2308	0.4615	0.3077	0.5465	0.7162
0.0049	26.0	3250	0.5581	0.6149	0.6908	0.6507	0.9155	0.5947	0.7117	0.6480	0.1786	0.2	0.1887	0.8982	0.9259	0.9119	0.3659	0.2174	0.2727	0.3421	0.4815	0.4000	0.7431	0.8088	0.7746	0.2273	0.2	0.2128	0.9509	0.9568	0.9538	0.6364	0.3182	0.4242	0.5769	0.5556	0.5660	0.5833	0.7	0.6364	0.1852	0.2083	0.1961	0.9036	0.9259	0.9146	0.4643	0.2281	0.3059	0.24	0.4615	0.3158	0.5300	0.7079
0.0049	27.0	3375	0.5642	0.6164	0.6806	0.6469	0.9156	0.5895	0.6917	0.6365	0.1786	0.2	0.1887	0.8824	0.9259	0.9036	0.4722	0.2464	0.3238	0.3784	0.5185	0.4375	0.7529	0.7982	0.7749	0.2273	0.2	0.2128	0.9398	0.9630	0.9512	0.7	0.3182	0.4375	0.6538	0.6296	0.6415	0.5774	0.664	0.6177	0.1786	0.2083	0.1923	0.9036	0.9259	0.9146	0.4839	0.2632	0.3409	0.2083	0.3846	0.2703	0.5354	0.7046
0.0036	28.0	3500	0.5611	0.6256	0.6965	0.6592	0.9153	0.5919	0.7083	0.6449	0.2	0.2	0.2000	0.9157	0.9383	0.9268	0.5122	0.3043	0.3818	0.3636	0.4444	0.4000	0.7384	0.8142	0.7744	0.2273	0.2	0.2128	0.9509	0.9568	0.9538	0.5897	0.3485	0.4381	0.64	0.5926	0.6154	0.5859	0.696	0.6362	0.2	0.2083	0.2041	0.9264	0.9321	0.9292	0.5625	0.3158	0.4045	0.1579	0.2308	0.1875	0.5356	0.7133
0.0036	29.0	3625	0.5777	0.6308	0.6965	0.6620	0.9138	0.6112	0.71	0.6569	0.1818	0.24	0.2069	0.9048	0.9383	0.9212	0.5	0.2754	0.3551	0.3077	0.4444	0.3636	0.7614	0.7965	0.7785	0.2	0.24	0.2182	0.9455	0.9630	0.9541	0.625	0.3030	0.4082	0.5714	0.5926	0.5818	0.5808	0.69	0.6307	0.1724	0.2083	0.1887	0.9157	0.9383	0.9268	0.5161	0.2807	0.3636	0.16	0.3077	0.2105	0.5261	0.7096
0.0036	30.0	3750	0.5546	0.6388	0.6931	0.6649	0.9169	0.6049	0.7017	0.6497	0.1786	0.2	0.1887	0.9268	0.9383	0.9325	0.5135	0.2754	0.3585	0.4545	0.5556	0.5	0.7615	0.7912	0.7760	0.2	0.2	0.2000	0.9689	0.9630	0.9659	0.6	0.3182	0.4158	0.6667	0.5926	0.6275	0.5914	0.686	0.6352	0.1852	0.2083	0.1961	0.9325	0.9383	0.9354	0.5667	0.2982	0.3908	0.2632	0.3846	0.3125	0.5455	0.7149
0.0036	31.0	3875	0.5646	0.6142	0.6976	0.6532	0.9170	0.5891	0.7217	0.6487	0.1875	0.24	0.2105	0.9152	0.9321	0.9235	0.3784	0.2029	0.2642	0.3529	0.4444	0.3934	0.7378	0.8265	0.7796	0.2727	0.24	0.2553	0.9568	0.9568	0.9568	0.6552	0.2879	0.4	0.6522	0.5556	0.6	0.5796	0.706	0.6366	0.1852	0.2083	0.1961	0.9207	0.9321	0.9264	0.4483	0.2281	0.3023	0.2273	0.3846	0.2857	0.5339	0.7111
0.0032	32.0	4000	0.5708	0.6198	0.7033	0.6589	0.9166	0.5870	0.725	0.6488	0.1923	0.2	0.1961	0.9268	0.9383	0.9325	0.5	0.2609	0.3429	0.3143	0.4074	0.3548	0.7228	0.8354	0.7750	0.2273	0.2	0.2128	0.9688	0.9568	0.9627	0.6176	0.3182	0.4200	0.6	0.5556	0.5769	0.5870	0.702	0.6393	0.2083	0.2083	0.2083	0.9207	0.9321	0.9264	0.5517	0.2807	0.3721	0.1905	0.3077	0.2353	0.5329	0.7130
0.0032	33.0	4125	0.5836	0.6207	0.6931	0.6549	0.9149	0.5950	0.71	0.6474	0.1875	0.24	0.2105	0.9157	0.9383	0.9268	0.4286	0.2174	0.2885	0.3514	0.4815	0.4062	0.7428	0.8177	0.7784	0.2222	0.24	0.2308	0.9571	0.9630	0.9600	0.6	0.2727	0.3750	0.6154	0.5926	0.6038	0.5874	0.692	0.6354	0.1724	0.2083	0.1887	0.9157	0.9383	0.9268	0.4483	0.2281	0.3023	0.1905	0.3077	0.2353	0.5237	0.7088
0.0032	34.0	4250	0.5745	0.6213	0.6931	0.6552	0.9168	0.5961	0.7133	0.6495	0.1724	0.2	0.1852	0.9212	0.9383	0.9297	0.4054	0.2174	0.2830	0.3333	0.4444	0.3810	0.7476	0.8230	0.7835	0.2083	0.2	0.2041	0.9630	0.9630	0.9630	0.5938	0.2879	0.3878	0.625	0.5556	0.5882	0.5891	0.694	0.6373	0.1852	0.2083	0.1961	0.9212	0.9383	0.9297	0.4828	0.2456	0.3256	0.1739	0.3077	0.2222	0.5237	0.7125
0.0032	35.0	4375	0.5777	0.6122	0.6920	0.6497	0.9160	0.5871	0.7133	0.6441	0.1724	0.2	0.1852	0.9212	0.9383	0.9297	0.3846	0.2174	0.2778	0.3056	0.4074	0.3492	0.7373	0.8248	0.7786	0.2083	0.2	0.2041	0.9630	0.9630	0.9630	0.5758	0.2879	0.3838	0.6522	0.5556	0.6	0.5786	0.692	0.6302	0.1852	0.2083	0.1961	0.9212	0.9383	0.9297	0.4516	0.2456	0.3182	0.1739	0.3077	0.2222	0.5226	0.7083
0.0022	36.0	4500	0.5876	0.6171	0.6954	0.6539	0.9170	0.5970	0.7183	0.6520	0.1613	0.2	0.1786	0.9207	0.9321	0.9264	0.4	0.2319	0.2936	0.2895	0.4074	0.3385	0.7484	0.8212	0.7831	0.2	0.2	0.2000	0.9627	0.9568	0.9598	0.5714	0.3030	0.3960	0.6	0.5556	0.5769	0.5875	0.698	0.6380	0.1724	0.2083	0.1887	0.9207	0.9321	0.9264	0.4516	0.2456	0.3182	0.1538	0.3077	0.2051	0.5192	0.7115
0.0022	37.0	4625	0.5922	0.6194	0.6931	0.6542	0.9153	0.5975	0.715	0.6510	0.1613	0.2	0.1786	0.9207	0.9321	0.9264	0.4103	0.2319	0.2963	0.3056	0.4074	0.3492	0.7549	0.8124	0.7826	0.2	0.2	0.2000	0.9627	0.9568	0.9598	0.5882	0.3030	0.4000	0.6	0.5556	0.5769	0.5728	0.692	0.6268	0.1786	0.2083	0.1923	0.9207	0.9321	0.9264	0.4516	0.2456	0.3182	0.1667	0.3077	0.2162	0.5199	0.7081
0.0022	38.0	4750	0.5959	0.6136	0.6942	0.6514	0.9152	0.5961	0.7183	0.6515	0.1613	0.2	0.1786	0.9042	0.9321	0.9179	0.375	0.2174	0.2752	0.2895	0.4074	0.3385	0.7408	0.8195	0.7782	0.2	0.2	0.2000	0.9512	0.9630	0.9571	0.5882	0.3030	0.4000	0.5769	0.5556	0.5660	0.5819	0.696	0.6339	0.1724	0.2083	0.1887	0.9042	0.9321	0.9179	0.4194	0.2281	0.2955	0.16	0.3077	0.2105	0.5148	0.7065
0.0022	39.0	4875	0.5967	0.6132	0.6931	0.6507	0.9156	0.5964	0.7167	0.6510	0.1562	0.2	0.1754	0.9096	0.9321	0.9207	0.375	0.2174	0.2752	0.2821	0.4074	0.3333	0.7444	0.8195	0.7801	0.2	0.2	0.2000	0.9571	0.9630	0.9600	0.5882	0.3030	0.4000	0.5556	0.5556	0.5556	0.5839	0.696	0.6350	0.1667	0.2083	0.1852	0.9096	0.9321	0.9207	0.4194	0.2281	0.2955	0.16	0.3077	0.2105	0.5143	0.7079
0.0017	40.0	5000	0.5960	0.6145	0.6931	0.6514	0.9158	0.5972	0.7167	0.6515	0.1613	0.2	0.1786	0.9042	0.9321	0.9179	0.375	0.2174	0.2752	0.2895	0.4074	0.3385	0.7488	0.8177	0.7817	0.2083	0.2	0.2041	0.9512	0.9630	0.9571	0.5882	0.3030	0.4000	0.5769	0.5556	0.5660	0.5822	0.694	0.6332	0.1667	0.2083	0.1852	0.9096	0.9321	0.9207	0.4194	0.2281	0.2955	0.16	0.3077	0.2105	0.5154	0.7079

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0

csNoHug/bert-base-cased-finetuned-ner-cadec

bert-base-cased-finetuned-ner-cadec

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Seed this model