albert-base-v2-finetuned-ner-cadec

This model is a fine-tuned version of albert-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.6830
Precision: 0.6428
Recall: 0.6704
F1: 0.6563
Accuracy: 0.9147
Adr Precision: 0.6180
Adr Recall: 0.6767
Adr F1: 0.6460
Disease Precision: 0.2581
Disease Recall: 0.32
Disease F1: 0.2857
Drug Precision: 0.9036
Drug Recall: 0.9259
Drug F1: 0.9146
Finding Precision: 0.4054
Finding Recall: 0.2174
Finding F1: 0.2830
Symptom Precision: 0.4333
Symptom Recall: 0.4815
Symptom F1: 0.4561
B-adr Precision: 0.7509
B-adr Recall: 0.7735
B-adr F1: 0.7620
B-disease Precision: 0.2667
B-disease Recall: 0.32
B-disease F1: 0.2909
B-drug Precision: 0.9563
B-drug Recall: 0.9444
B-drug F1: 0.9503
B-finding Precision: 0.5312
B-finding Recall: 0.2576
B-finding F1: 0.3469
B-symptom Precision: 0.5
B-symptom Recall: 0.5185
B-symptom F1: 0.5091
I-adr Precision: 0.5959
I-adr Recall: 0.6578
I-adr F1: 0.6254
I-disease Precision: 0.2174
I-disease Recall: 0.2381
I-disease F1: 0.2273
I-drug Precision: 0.9096
I-drug Recall: 0.9379
I-drug F1: 0.9235
I-finding Precision: 0.4
I-finding Recall: 0.1923
I-finding F1: 0.2597
I-symptom Precision: 0.375
I-symptom Recall: 0.4286
I-symptom F1: 0.4000
Macro Avg F1: 0.5295
Weighted Avg F1: 0.6995

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	0.3036	0.4900	0.5855	0.5335	0.8983	0.4564	0.6017	0.5191	0.0877	0.2	0.1220	0.8671	0.9259	0.8955	0.0294	0.0145	0.0194	0.0	0.0	0.0	0.6901	0.7805	0.7326	0.2	0.2	0.2000	0.9112	0.9506	0.9305	0.5	0.0152	0.0294	0.0	0.0	0.0	0.4781	0.5784	0.5235	0.0652	0.1429	0.0896	0.8830	0.9379	0.9096	0.1818	0.1154	0.1412	0.0	0.0	0.0	0.3556	0.6214
No log	2.0	250	0.2758	0.5594	0.6297	0.5924	0.9070	0.5310	0.6717	0.5931	0.1081	0.16	0.1290	0.8421	0.8889	0.8649	0.16	0.0580	0.0851	0.5	0.0370	0.0690	0.7317	0.7965	0.7627	0.2308	0.24	0.2353	0.9804	0.9259	0.9524	0.5385	0.1061	0.1772	1.0	0.0741	0.1379	0.5274	0.6660	0.5887	0.0952	0.0952	0.0952	0.8471	0.8944	0.8701	0.3125	0.0962	0.1471	0.0	0.0	0.0	0.3967	0.6599
No log	3.0	375	0.2840	0.5713	0.6489	0.6076	0.9079	0.5533	0.675	0.6081	0.1667	0.32	0.2192	0.8571	0.9259	0.8902	0.1842	0.1014	0.1308	0.3	0.1111	0.1622	0.7298	0.7982	0.7625	0.2162	0.32	0.2581	0.9281	0.9568	0.9422	0.4583	0.1667	0.2444	0.7	0.2593	0.3784	0.5482	0.6599	0.5989	0.1842	0.3333	0.2373	0.8671	0.9317	0.8982	0.2609	0.1154	0.16	0.0	0.0	0.0	0.4480	0.6744
0.2544	4.0	500	0.2906	0.5760	0.6353	0.6042	0.9104	0.5679	0.6483	0.6054	0.0816	0.16	0.1081	0.8862	0.9136	0.8997	0.2364	0.1884	0.2097	0.3889	0.2593	0.3111	0.7626	0.7788	0.7706	0.1875	0.24	0.2105	0.9379	0.9321	0.9350	0.4474	0.2576	0.3269	0.7333	0.4074	0.5238	0.5647	0.6314	0.5962	0.1579	0.2857	0.2034	0.8916	0.9193	0.9052	0.3143	0.2115	0.2529	0.6667	0.1429	0.2353	0.4960	0.6862
0.2544	5.0	625	0.2948	0.5855	0.6750	0.6270	0.9132	0.5633	0.6967	0.6230	0.0333	0.04	0.0364	0.8786	0.9383	0.9075	0.2549	0.1884	0.2167	0.5455	0.4444	0.4898	0.7312	0.8088	0.7681	0.2083	0.2	0.2041	0.9118	0.9568	0.9337	0.5161	0.2424	0.3299	0.7778	0.5185	0.6222	0.5507	0.6741	0.6062	0.0667	0.0476	0.0556	0.8994	0.9441	0.9212	0.3077	0.2308	0.2637	0.625	0.3571	0.4545	0.5159	0.6920
0.2544	6.0	750	0.3172	0.6092	0.6569	0.6322	0.9130	0.5859	0.665	0.6230	0.2093	0.36	0.2647	0.8922	0.9198	0.9058	0.4074	0.1594	0.2292	0.3529	0.4444	0.3934	0.7616	0.7858	0.7735	0.2778	0.4	0.3279	0.9333	0.9506	0.9419	0.6471	0.1667	0.2651	0.6667	0.5185	0.5833	0.5762	0.6619	0.6161	0.2333	0.3333	0.2745	0.9030	0.9255	0.9141	0.4762	0.1923	0.2740	0.2174	0.3571	0.2703	0.5241	0.6973
0.2544	7.0	875	0.3519	0.5992	0.6670	0.6313	0.9127	0.5663	0.6833	0.6193	0.1471	0.2	0.1695	0.9042	0.9321	0.9179	0.3947	0.2174	0.2804	0.4	0.2963	0.3404	0.7245	0.8283	0.7729	0.2593	0.28	0.2692	0.9448	0.9506	0.9477	0.6538	0.2576	0.3696	0.7857	0.4074	0.5366	0.5613	0.6619	0.6075	0.1818	0.1905	0.1860	0.9146	0.9317	0.9231	0.4138	0.2308	0.2963	0.2308	0.2143	0.2222	0.5131	0.6977
0.0853	8.0	1000	0.3881	0.5996	0.6546	0.6259	0.9138	0.5928	0.655	0.6223	0.0769	0.12	0.0938	0.8817	0.9198	0.9003	0.3284	0.3188	0.3235	0.4231	0.4074	0.4151	0.7560	0.7788	0.7672	0.25	0.32	0.2807	0.9337	0.9568	0.9451	0.5957	0.4242	0.4956	0.6190	0.4815	0.5417	0.5890	0.6334	0.6104	0.0417	0.0476	0.0444	0.8970	0.9193	0.9080	0.3654	0.3654	0.3654	0.4545	0.3571	0.4	0.5358	0.7022
0.0853	9.0	1125	0.4068	0.5875	0.6580	0.6207	0.9109	0.5625	0.66	0.6074	0.1818	0.4	0.2500	0.9146	0.9259	0.9202	0.3421	0.1884	0.2430	0.4286	0.4444	0.4364	0.7138	0.7947	0.7521	0.2340	0.44	0.3056	0.9390	0.9506	0.9448	0.6522	0.2273	0.3371	0.5714	0.4444	0.5	0.5546	0.6314	0.5905	0.1944	0.3333	0.2456	0.9202	0.9317	0.9259	0.3929	0.2115	0.275	0.3158	0.4286	0.3636	0.5240	0.6849
0.0853	10.0	1250	0.4256	0.6337	0.6682	0.6505	0.9140	0.6069	0.6717	0.6377	0.2432	0.36	0.2903	0.9130	0.9074	0.9102	0.4706	0.2319	0.3107	0.4286	0.5556	0.4839	0.7530	0.7717	0.7622	0.3125	0.4	0.3509	0.9497	0.9321	0.9408	0.6667	0.2424	0.3556	0.5152	0.6296	0.5667	0.5930	0.6558	0.6228	0.2609	0.2857	0.2727	0.9245	0.9130	0.9187	0.5769	0.2885	0.3846	0.4211	0.5714	0.4848	0.5660	0.7051
0.0853	11.0	1375	0.4426	0.6211	0.6387	0.6298	0.9093	0.5899	0.645	0.6162	0.1944	0.28	0.2295	0.8916	0.9136	0.9024	0.3929	0.1594	0.2268	0.5	0.4074	0.4490	0.7522	0.7469	0.7496	0.2059	0.28	0.2373	0.9383	0.9383	0.9383	0.5455	0.1818	0.2727	0.6667	0.4444	0.5333	0.5704	0.6191	0.5938	0.2	0.2381	0.2174	0.9080	0.9193	0.9136	0.5714	0.2308	0.3288	0.4286	0.4286	0.4286	0.5213	0.6819
0.0307	12.0	1500	0.4234	0.6211	0.6852	0.6516	0.9144	0.5848	0.6783	0.6281	0.2143	0.24	0.2264	0.9096	0.9321	0.9207	0.5	0.3913	0.4390	0.4667	0.5185	0.4912	0.7471	0.8	0.7726	0.2857	0.24	0.2609	0.9448	0.9506	0.9477	0.5957	0.4242	0.4956	0.6364	0.5185	0.5714	0.5754	0.6680	0.6183	0.2609	0.2857	0.2727	0.9207	0.9379	0.9292	0.5641	0.4231	0.4835	0.2857	0.4286	0.3429	0.5695	0.7156
0.0307	13.0	1625	0.4559	0.6220	0.6784	0.6490	0.9127	0.6059	0.6817	0.6416	0.2188	0.28	0.2456	0.9042	0.9321	0.9179	0.3846	0.2899	0.3306	0.3243	0.4444	0.375	0.7547	0.7841	0.7691	0.2667	0.32	0.2909	0.9448	0.9506	0.9477	0.5476	0.3485	0.4259	0.5161	0.5926	0.5517	0.6	0.6660	0.6313	0.16	0.1905	0.1739	0.9152	0.9379	0.9264	0.4474	0.3269	0.3778	0.1923	0.3571	0.25	0.5345	0.7098
0.0307	14.0	1750	0.4551	0.6031	0.6523	0.6268	0.9127	0.5842	0.6417	0.6116	0.1458	0.28	0.1918	0.9152	0.9321	0.9235	0.2979	0.2029	0.2414	0.5278	0.7037	0.6032	0.7496	0.7735	0.7613	0.2051	0.32	0.25	0.9565	0.9506	0.9536	0.5143	0.2727	0.3564	0.6	0.6667	0.6316	0.5768	0.6273	0.6010	0.1290	0.1905	0.1538	0.9264	0.9379	0.9321	0.3889	0.2692	0.3182	0.3478	0.5714	0.4324	0.5390	0.6960
0.0307	15.0	1875	0.4709	0.6046	0.6806	0.6404	0.9135	0.5872	0.6733	0.6273	0.1961	0.4	0.2632	0.8902	0.9506	0.9194	0.425	0.2464	0.3119	0.3810	0.5926	0.4638	0.7492	0.7929	0.7704	0.2128	0.4	0.2778	0.9286	0.9630	0.9455	0.5806	0.2727	0.3711	0.5758	0.7037	0.6333	0.5761	0.6395	0.6062	0.1892	0.3333	0.2414	0.9	0.9503	0.9245	0.4839	0.2885	0.3614	0.3214	0.6429	0.4286	0.5560	0.7029
0.0136	16.0	2000	0.5190	0.6193	0.6818	0.6491	0.9133	0.6	0.69	0.6419	0.2045	0.36	0.2609	0.8779	0.9321	0.9042	0.3824	0.1884	0.2524	0.4688	0.5556	0.5085	0.7401	0.7965	0.7673	0.2308	0.36	0.2812	0.9509	0.9568	0.9538	0.5357	0.2273	0.3191	0.6667	0.5926	0.6275	0.5875	0.6701	0.6261	0.2333	0.3333	0.2745	0.8895	0.9503	0.9189	0.5238	0.2115	0.3014	0.35	0.5	0.4118	0.5482	0.7043
0.0136	17.0	2125	0.5312	0.6206	0.6818	0.6498	0.9154	0.5974	0.695	0.6425	0.2105	0.32	0.2540	0.9259	0.9259	0.9259	0.3846	0.2174	0.2778	0.3636	0.4444	0.4000	0.7302	0.8	0.7635	0.2857	0.4	0.3333	0.9563	0.9444	0.9503	0.5926	0.2424	0.3441	0.6087	0.5185	0.5600	0.5832	0.6497	0.6146	0.2	0.2381	0.2174	0.9371	0.9255	0.9313	0.4062	0.25	0.3095	0.2727	0.4286	0.3333	0.5357	0.6998
0.0136	18.0	2250	0.5362	0.6235	0.6546	0.6387	0.9127	0.5976	0.6533	0.6242	0.2581	0.32	0.2857	0.9096	0.9321	0.9207	0.4186	0.2609	0.3214	0.2903	0.3333	0.3103	0.7513	0.7646	0.7579	0.2667	0.32	0.2909	0.9627	0.9568	0.9598	0.5556	0.3030	0.3922	0.44	0.4074	0.4231	0.5830	0.6293	0.6053	0.2632	0.2381	0.25	0.9202	0.9317	0.9259	0.4688	0.2885	0.3571	0.2273	0.3571	0.2778	0.5240	0.6959
0.0136	19.0	2375	0.5420	0.6261	0.6297	0.6279	0.9154	0.5917	0.64	0.6149	0.1944	0.28	0.2295	0.9423	0.9074	0.9245	0.2857	0.0870	0.1333	0.4615	0.4444	0.4528	0.7645	0.7469	0.7556	0.2424	0.32	0.2759	0.9744	0.9383	0.9560	0.3889	0.1061	0.1667	0.5833	0.5185	0.5490	0.5704	0.6191	0.5938	0.2083	0.2381	0.2222	0.9484	0.9130	0.9304	0.375	0.1154	0.1765	0.3333	0.4286	0.375	0.5001	0.6786
0.0059	20.0	2500	0.5872	0.6138	0.6874	0.6485	0.9106	0.6011	0.7083	0.6503	0.1628	0.28	0.2059	0.9042	0.9321	0.9179	0.3243	0.1739	0.2264	0.3429	0.4444	0.3871	0.7212	0.8195	0.7672	0.25	0.4	0.3077	0.9394	0.9568	0.9480	0.4828	0.2121	0.2947	0.56	0.5185	0.5385	0.5819	0.6660	0.6211	0.1379	0.1905	0.16	0.9036	0.9317	0.9174	0.3571	0.1923	0.25	0.25	0.4286	0.3158	0.5120	0.6958
0.0059	21.0	2625	0.5642	0.6088	0.6557	0.6314	0.9126	0.5913	0.6533	0.6207	0.2	0.36	0.2571	0.9080	0.9136	0.9108	0.4286	0.2174	0.2885	0.3333	0.5556	0.4167	0.7671	0.7752	0.7711	0.2381	0.4	0.2985	0.9441	0.9383	0.9412	0.6897	0.3030	0.4211	0.4595	0.6296	0.5312	0.5730	0.6314	0.6008	0.1818	0.2857	0.2222	0.9141	0.9255	0.9198	0.4286	0.2308	0.3	0.2308	0.4286	0.3	0.5306	0.6978
0.0059	22.0	2750	0.5869	0.6190	0.6716	0.6442	0.9133	0.6092	0.6833	0.6441	0.1951	0.32	0.2424	0.9030	0.9198	0.9113	0.2895	0.1594	0.2056	0.3659	0.5556	0.4412	0.7564	0.7805	0.7683	0.2308	0.36	0.2812	0.9444	0.9444	0.9444	0.5714	0.2424	0.3404	0.5484	0.6296	0.5862	0.5930	0.6558	0.6228	0.1562	0.2381	0.1887	0.9030	0.9255	0.9141	0.2414	0.1346	0.1728	0.2593	0.5	0.3415	0.5161	0.6964
0.0059	23.0	2875	0.5873	0.6149	0.6546	0.6341	0.9112	0.5964	0.655	0.6243	0.2105	0.32	0.2540	0.9096	0.9321	0.9207	0.4	0.2029	0.2692	0.2857	0.4444	0.3478	0.7597	0.7611	0.7604	0.2222	0.32	0.2623	0.9390	0.9506	0.9448	0.7	0.3182	0.4375	0.4828	0.5185	0.5	0.5680	0.6212	0.5934	0.2222	0.2857	0.25	0.9146	0.9317	0.9231	0.4783	0.2115	0.2933	0.1875	0.4286	0.2609	0.5226	0.6917
0.0024	24.0	3000	0.6273	0.6126	0.6806	0.6448	0.9103	0.5983	0.695	0.6430	0.1842	0.28	0.2222	0.8929	0.9259	0.9091	0.3171	0.1884	0.2364	0.3784	0.5185	0.4375	0.7234	0.8053	0.7621	0.2581	0.32	0.2857	0.9390	0.9506	0.9448	0.5455	0.2727	0.3636	0.5161	0.5926	0.5517	0.5893	0.6721	0.6280	0.1923	0.2381	0.2128	0.9042	0.9379	0.9207	0.375	0.1731	0.2368	0.2857	0.4286	0.3429	0.5249	0.6994
0.0024	25.0	3125	0.6096	0.6133	0.6682	0.6396	0.9102	0.5985	0.6783	0.6359	0.1892	0.28	0.2258	0.8976	0.9198	0.9085	0.2955	0.1884	0.2301	0.4	0.5185	0.4516	0.7534	0.7788	0.7659	0.2286	0.32	0.2667	0.9503	0.9444	0.9474	0.4857	0.2576	0.3366	0.5769	0.5556	0.5660	0.5750	0.6477	0.6092	0.1481	0.1905	0.1667	0.9091	0.9317	0.9202	0.2903	0.1731	0.2169	0.2	0.3571	0.2564	0.5052	0.6919
0.0024	26.0	3250	0.6085	0.6352	0.6784	0.6561	0.9153	0.6150	0.6817	0.6466	0.2162	0.32	0.2581	0.8876	0.9259	0.9063	0.4359	0.2464	0.3148	0.4545	0.5556	0.5	0.7695	0.7858	0.7776	0.2353	0.32	0.2712	0.9277	0.9506	0.9390	0.6111	0.3333	0.4314	0.6154	0.5926	0.6038	0.6011	0.6660	0.6319	0.1923	0.2381	0.2128	0.8994	0.9441	0.9212	0.4231	0.2115	0.2821	0.3158	0.4286	0.3636	0.5434	0.7107
0.0024	27.0	3375	0.6359	0.6191	0.6682	0.6427	0.9123	0.6015	0.6767	0.6369	0.1842	0.28	0.2222	0.9091	0.9259	0.9174	0.3171	0.1884	0.2364	0.4118	0.5185	0.4590	0.7383	0.7841	0.7605	0.2353	0.32	0.2712	0.9387	0.9444	0.9415	0.5625	0.2727	0.3673	0.5357	0.5556	0.5455	0.5849	0.6456	0.6137	0.1538	0.1905	0.1702	0.9085	0.9255	0.9169	0.36	0.1731	0.2338	0.2609	0.4286	0.3243	0.5145	0.6927
0.0012	28.0	3500	0.6558	0.6220	0.6670	0.6437	0.9129	0.6080	0.68	0.6420	0.1707	0.28	0.2121	0.9030	0.9198	0.9113	0.3421	0.1884	0.2430	0.375	0.4444	0.4068	0.7688	0.7770	0.7729	0.2286	0.32	0.2667	0.9387	0.9444	0.9415	0.5758	0.2879	0.3838	0.5185	0.5185	0.5185	0.5814	0.6619	0.6190	0.1613	0.2381	0.1923	0.9085	0.9255	0.9169	0.3636	0.1538	0.2162	0.3	0.4286	0.3529	0.5181	0.6989
0.0012	29.0	3625	0.6434	0.6277	0.6625	0.6446	0.9142	0.6054	0.67	0.6361	0.175	0.28	0.2154	0.9030	0.9198	0.9113	0.4	0.1739	0.2424	0.4545	0.5556	0.5	0.7599	0.7788	0.7692	0.2571	0.36	0.3	0.9444	0.9444	0.9444	0.625	0.2273	0.3333	0.5517	0.5926	0.5714	0.5824	0.6477	0.6133	0.1379	0.1905	0.16	0.9085	0.9255	0.9169	0.4	0.1538	0.2222	0.3333	0.4286	0.375	0.5206	0.6954
0.0012	30.0	3750	0.6456	0.6324	0.6625	0.6471	0.9152	0.6076	0.6683	0.6365	0.1892	0.28	0.2258	0.9036	0.9259	0.9146	0.4	0.2029	0.2692	0.4815	0.4815	0.4815	0.7570	0.7611	0.7590	0.2353	0.32	0.2712	0.9273	0.9444	0.9358	0.5484	0.2576	0.3505	0.6087	0.5185	0.5600	0.5860	0.6456	0.6143	0.1481	0.1905	0.1667	0.9030	0.9255	0.9141	0.4091	0.1731	0.2432	0.3529	0.4286	0.3871	0.5202	0.6918
0.0012	31.0	3875	0.6698	0.6266	0.6670	0.6462	0.9126	0.6048	0.6733	0.6372	0.2	0.28	0.2333	0.8982	0.9259	0.9119	0.3590	0.2029	0.2593	0.4516	0.5185	0.4828	0.7513	0.7805	0.7656	0.2581	0.32	0.2857	0.9333	0.9506	0.9419	0.5152	0.2576	0.3434	0.5357	0.5556	0.5455	0.5839	0.6517	0.6160	0.1667	0.1905	0.1778	0.8982	0.9317	0.9146	0.4348	0.1923	0.2667	0.3529	0.4286	0.3871	0.5244	0.6960
0.0006	32.0	4000	0.6512	0.6253	0.6727	0.6481	0.9143	0.6119	0.6833	0.6457	0.1842	0.28	0.2222	0.9042	0.9321	0.9179	0.3171	0.1884	0.2364	0.3824	0.4815	0.4262	0.7539	0.7752	0.7644	0.2353	0.32	0.2712	0.9387	0.9444	0.9415	0.5152	0.2576	0.3434	0.5357	0.5556	0.5455	0.5851	0.6578	0.6194	0.1481	0.1905	0.1667	0.9036	0.9317	0.9174	0.3704	0.1923	0.2532	0.3	0.4286	0.3529	0.5176	0.6957
0.0006	33.0	4125	0.6629	0.6432	0.6636	0.6533	0.9169	0.6289	0.6667	0.6472	0.2059	0.28	0.2373	0.9036	0.9259	0.9146	0.3721	0.2319	0.2857	0.4062	0.4815	0.4407	0.7822	0.7628	0.7724	0.2581	0.32	0.2857	0.9273	0.9444	0.9358	0.6316	0.3636	0.4615	0.5769	0.5556	0.5660	0.6031	0.6436	0.6227	0.1538	0.1905	0.1702	0.9091	0.9317	0.9202	0.3929	0.2115	0.275	0.2727	0.4286	0.3333	0.5343	0.7054
0.0006	34.0	4250	0.6629	0.6356	0.6716	0.6531	0.9149	0.6138	0.6833	0.6467	0.2059	0.28	0.2373	0.9091	0.9259	0.9174	0.3514	0.1884	0.2453	0.4483	0.4815	0.4643	0.75	0.7752	0.7624	0.2581	0.32	0.2857	0.9503	0.9444	0.9474	0.5152	0.2576	0.3434	0.56	0.5185	0.5385	0.5923	0.6599	0.6243	0.2	0.2381	0.2174	0.9152	0.9379	0.9264	0.3913	0.1731	0.24	0.375	0.4286	0.4000	0.5285	0.6988
0.0006	35.0	4375	0.6643	0.6373	0.6727	0.6545	0.9155	0.6156	0.6833	0.6477	0.2059	0.28	0.2373	0.9036	0.9259	0.9146	0.3514	0.1884	0.2453	0.4828	0.5185	0.5	0.7509	0.7735	0.7620	0.2581	0.32	0.2857	0.9444	0.9444	0.9444	0.5	0.2576	0.3400	0.5769	0.5556	0.5660	0.5905	0.6578	0.6224	0.2	0.2381	0.2174	0.9096	0.9379	0.9235	0.3913	0.1731	0.24	0.4	0.4286	0.4138	0.5315	0.6979
0.0005	36.0	4500	0.6727	0.6329	0.6716	0.6516	0.9140	0.6077	0.6817	0.6426	0.2424	0.32	0.2759	0.9091	0.9259	0.9174	0.3421	0.1884	0.2430	0.4643	0.4815	0.4727	0.7457	0.7735	0.7593	0.2581	0.32	0.2857	0.9563	0.9444	0.9503	0.5	0.2424	0.3265	0.56	0.5185	0.5385	0.5794	0.6538	0.6144	0.2083	0.2381	0.2222	0.9152	0.9379	0.9264	0.4	0.1923	0.2597	0.3529	0.4286	0.3871	0.5270	0.6948
0.0005	37.0	4625	0.6779	0.6390	0.6716	0.6549	0.9142	0.6150	0.6817	0.6466	0.2424	0.32	0.2759	0.9091	0.9259	0.9174	0.3611	0.1884	0.2476	0.4483	0.4815	0.4643	0.7470	0.7735	0.76	0.2581	0.32	0.2857	0.9563	0.9444	0.9503	0.5	0.2273	0.3125	0.5185	0.5185	0.5185	0.5894	0.6578	0.6218	0.2083	0.2381	0.2222	0.9152	0.9379	0.9264	0.4167	0.1923	0.2632	0.375	0.4286	0.4000	0.5261	0.6967
0.0005	38.0	4750	0.6804	0.6429	0.6727	0.6574	0.9147	0.6210	0.68	0.6492	0.25	0.32	0.2807	0.9036	0.9259	0.9146	0.3684	0.2029	0.2617	0.4516	0.5185	0.4828	0.7534	0.7735	0.7633	0.2581	0.32	0.2857	0.9563	0.9444	0.9503	0.5	0.2576	0.3400	0.5172	0.5556	0.5357	0.5967	0.6599	0.6267	0.2174	0.2381	0.2273	0.9096	0.9379	0.9235	0.4	0.1923	0.2597	0.3529	0.4286	0.3871	0.5299	0.7004
0.0005	39.0	4875	0.6818	0.6421	0.6704	0.6560	0.9147	0.6170	0.6767	0.6455	0.2581	0.32	0.2857	0.9036	0.9259	0.9146	0.4054	0.2174	0.2830	0.4333	0.4815	0.4561	0.7522	0.7735	0.7627	0.2667	0.32	0.2909	0.9563	0.9444	0.9503	0.5294	0.2727	0.36	0.5	0.5185	0.5091	0.5938	0.6578	0.6242	0.2174	0.2381	0.2273	0.9096	0.9379	0.9235	0.4	0.1923	0.2597	0.375	0.4286	0.4000	0.5308	0.6999
0.0002	40.0	5000	0.6830	0.6428	0.6704	0.6563	0.9147	0.6180	0.6767	0.6460	0.2581	0.32	0.2857	0.9036	0.9259	0.9146	0.4054	0.2174	0.2830	0.4333	0.4815	0.4561	0.7509	0.7735	0.7620	0.2667	0.32	0.2909	0.9563	0.9444	0.9503	0.5312	0.2576	0.3469	0.5	0.5185	0.5091	0.5959	0.6578	0.6254	0.2174	0.2381	0.2273	0.9096	0.9379	0.9235	0.4	0.1923	0.2597	0.375	0.4286	0.4000	0.5295	0.6995

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0

csNoHug/albert-base-v2-finetuned-ner-cadec

albert-base-v2-finetuned-ner-cadec

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Seed this model