bsc-bio-ehr-es-finetuned-clinais-augmented2

This model is a fine-tuned version of joheras/bsc-bio-ehr-es-finetuned-clinais on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.3136
Precision: 0.4988
Recall: 0.6452
F1: 0.5626
Accuracy: 0.8593

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: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	114	0.7550	0.1166	0.1605	0.1351	0.7937
No log	2.0	228	0.6577	0.2096	0.2904	0.2435	0.8123
No log	3.0	342	0.5928	0.2167	0.3157	0.2570	0.8197
No log	4.0	456	0.5837	0.2532	0.3791	0.3036	0.8374
0.5045	5.0	570	0.5758	0.3309	0.5206	0.4046	0.8479
0.5045	6.0	684	0.6266	0.3506	0.5216	0.4194	0.8384
0.5045	7.0	798	0.6329	0.3503	0.5586	0.4306	0.8486
0.5045	8.0	912	0.6251	0.3769	0.5639	0.4518	0.8565
0.1043	9.0	1026	0.6509	0.3999	0.5945	0.4781	0.8582
0.1043	10.0	1140	0.7431	0.3755	0.5734	0.4538	0.8453
0.1043	11.0	1254	0.7000	0.4181	0.6061	0.4948	0.8598
0.1043	12.0	1368	0.7232	0.4375	0.6315	0.5169	0.8574
0.1043	13.0	1482	0.7741	0.4568	0.6199	0.5260	0.8596
0.0344	14.0	1596	0.8108	0.4661	0.6251	0.5341	0.8528
0.0344	15.0	1710	0.7922	0.4516	0.6209	0.5229	0.8613
0.0344	16.0	1824	0.8318	0.4727	0.6315	0.5407	0.8566
0.0344	17.0	1938	0.8579	0.4887	0.6378	0.5534	0.8558
0.0158	18.0	2052	0.8745	0.4626	0.6209	0.5302	0.8539
0.0158	19.0	2166	0.8959	0.4461	0.6167	0.5177	0.8530
0.0158	20.0	2280	0.9600	0.4442	0.6135	0.5153	0.8490
0.0158	21.0	2394	0.8769	0.4578	0.6294	0.5300	0.8601
0.0095	22.0	2508	0.9427	0.4503	0.6125	0.5190	0.8516
0.0095	23.0	2622	0.9188	0.4793	0.6367	0.5469	0.8582
0.0095	24.0	2736	0.9538	0.4790	0.6367	0.5467	0.8556
0.0095	25.0	2850	0.9785	0.4775	0.6262	0.5418	0.8495
0.0095	26.0	2964	0.9745	0.4785	0.6463	0.5499	0.8514
0.0066	27.0	3078	1.0168	0.4909	0.6262	0.5503	0.8541
0.0066	28.0	3192	0.9852	0.4796	0.6452	0.5502	0.8515
0.0066	29.0	3306	1.0372	0.4711	0.6367	0.5415	0.8526
0.0066	30.0	3420	1.0234	0.5012	0.6399	0.5622	0.8530
0.0045	31.0	3534	1.0058	0.4944	0.6484	0.5610	0.8582
0.0045	32.0	3648	1.0212	0.4776	0.6420	0.5477	0.8559
0.0045	33.0	3762	1.0301	0.4643	0.6378	0.5374	0.8533
0.0045	34.0	3876	1.0545	0.4740	0.6346	0.5427	0.8529
0.0045	35.0	3990	1.0632	0.4703	0.6272	0.5376	0.8524
0.0059	36.0	4104	1.0351	0.4923	0.6389	0.5561	0.8568
0.0059	37.0	4218	1.0584	0.4665	0.6177	0.5316	0.8545
0.0059	38.0	4332	1.0513	0.4695	0.6251	0.5362	0.8566
0.0059	39.0	4446	1.0482	0.4740	0.6357	0.5431	0.8555
0.0028	40.0	4560	1.0777	0.4899	0.6378	0.5541	0.8590
0.0028	41.0	4674	1.1045	0.5066	0.6505	0.5696	0.8589
0.0028	42.0	4788	1.0910	0.5	0.6441	0.5630	0.8556
0.0028	43.0	4902	1.1249	0.4809	0.6389	0.5488	0.8546
0.0021	44.0	5016	1.0668	0.4806	0.6283	0.5446	0.8591
0.0021	45.0	5130	1.0699	0.5033	0.6536	0.5687	0.8586
0.0021	46.0	5244	1.1457	0.5004	0.6410	0.5620	0.8526
0.0021	47.0	5358	1.1226	0.4858	0.6336	0.5500	0.8501
0.0021	48.0	5472	1.1459	0.4963	0.6399	0.5590	0.8532
0.0045	49.0	5586	1.1515	0.4919	0.6441	0.5578	0.8508
0.0045	50.0	5700	1.1952	0.4887	0.6420	0.5550	0.8561
0.0045	51.0	5814	1.1382	0.5042	0.6294	0.5599	0.8601
0.0045	52.0	5928	1.1547	0.4757	0.6315	0.5426	0.8585
0.0017	53.0	6042	1.2089	0.4996	0.6188	0.5528	0.8511
0.0017	54.0	6156	1.1838	0.4910	0.6357	0.5541	0.8555
0.0017	55.0	6270	1.2072	0.4907	0.6378	0.5546	0.8572
0.0017	56.0	6384	1.1894	0.5012	0.6505	0.5662	0.8605
0.0017	57.0	6498	1.2195	0.4992	0.6441	0.5625	0.8543
0.002	58.0	6612	1.1838	0.5008	0.6484	0.5651	0.8579
0.002	59.0	6726	1.2107	0.5029	0.6484	0.5664	0.8561
0.002	60.0	6840	1.1850	0.5	0.6505	0.5654	0.8581
0.002	61.0	6954	1.1926	0.5004	0.6431	0.5628	0.8571
0.002	62.0	7068	1.2789	0.5062	0.6431	0.5665	0.8524
0.002	63.0	7182	1.2268	0.4939	0.6452	0.5595	0.8562
0.002	64.0	7296	1.2729	0.5103	0.6515	0.5724	0.8531
0.002	65.0	7410	1.2667	0.5127	0.6410	0.5697	0.8530
0.0016	66.0	7524	1.2580	0.5142	0.6484	0.5736	0.8528
0.0016	67.0	7638	1.2323	0.4839	0.6494	0.5546	0.8567
0.0016	68.0	7752	1.2647	0.4951	0.6399	0.5583	0.8514
0.0016	69.0	7866	1.2604	0.5178	0.6463	0.5749	0.8563
0.0016	70.0	7980	1.2154	0.4996	0.6410	0.5615	0.8596
0.0005	71.0	8094	1.2452	0.5066	0.6505	0.5696	0.8592
0.0005	72.0	8208	1.2100	0.4882	0.6357	0.5523	0.8609
0.0005	73.0	8322	1.2549	0.4936	0.6515	0.5617	0.8590
0.0005	74.0	8436	1.2600	0.5134	0.6463	0.5722	0.8617
0.0004	75.0	8550	1.3043	0.4939	0.6431	0.5587	0.8546
0.0004	76.0	8664	1.2772	0.4907	0.6389	0.5550	0.8591
0.0004	77.0	8778	1.3091	0.4955	0.6389	0.5581	0.8518
0.0004	78.0	8892	1.2821	0.4988	0.6452	0.5626	0.8565
0.0004	79.0	9006	1.2668	0.4984	0.6463	0.5628	0.8591
0.0004	80.0	9120	1.2872	0.5104	0.6463	0.5704	0.8567
0.0004	81.0	9234	1.2877	0.4919	0.6389	0.5558	0.8553
0.0004	82.0	9348	1.2701	0.5079	0.6441	0.5680	0.8587
0.0004	83.0	9462	1.3579	0.4972	0.6484	0.5628	0.8500
0.0004	84.0	9576	1.3292	0.5138	0.6494	0.5737	0.8542
0.0004	85.0	9690	1.3437	0.4963	0.6389	0.5586	0.8546
0.0004	86.0	9804	1.3193	0.5155	0.6505	0.5752	0.8577
0.0004	87.0	9918	1.3579	0.4919	0.6420	0.5570	0.8520
0.0003	88.0	10032	1.3109	0.5181	0.6494	0.5764	0.8585
0.0003	89.0	10146	1.2943	0.4876	0.6441	0.5551	0.8615
0.0003	90.0	10260	1.3132	0.4826	0.6463	0.5526	0.8574
0.0003	91.0	10374	1.3176	0.5058	0.6452	0.5671	0.8563
0.0003	92.0	10488	1.3130	0.4964	0.6463	0.5615	0.8583
0.0002	93.0	10602	1.3220	0.4992	0.6463	0.5633	0.8563
0.0002	94.0	10716	1.3160	0.5	0.6463	0.5638	0.8603
0.0002	95.0	10830	1.3155	0.4857	0.6473	0.5550	0.8615
0.0002	96.0	10944	1.3223	0.4912	0.6484	0.5589	0.8577
0.0002	97.0	11058	1.3138	0.5087	0.6484	0.5701	0.8593
0.0002	98.0	11172	1.3152	0.5037	0.6463	0.5661	0.8594
0.0002	99.0	11286	1.3137	0.4996	0.6452	0.5631	0.8593
0.0002	100.0	11400	1.3136	0.4988	0.6452	0.5626	0.8593

Framework versions

Transformers 4.25.1
Pytorch 1.13.0
Datasets 2.8.0
Tokenizers 0.12.1

joheras/bsc-bio-ehr-es-finetuned-clinais-augmented2

bsc-bio-ehr-es-finetuned-clinais-augmented2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

为此模型做种