Training Loss	Epoch	Step	Validation Loss
3.2642	0.0103	100	2.9924
2.6906	0.0205	200	2.5289
2.4587	0.0308	300	2.3835
2.357	0.0411	400	2.3593
2.3804	0.0514	500	2.3834
2.3997	0.0616	600	2.4149
2.4127	0.0719	700	2.4326
2.4324	0.0822	800	2.4406
2.4394	0.0924	900	2.4357
2.4363	0.1027	1000	2.4273
2.4104	0.1130	1100	2.4209
2.4255	0.1232	1200	2.4175
2.4019	0.1335	1300	2.4075
2.4133	0.1438	1400	2.4035
2.3963	0.1541	1500	2.3965
2.3874	0.1643	1600	2.3951
2.382	0.1746	1700	2.3907
2.3827	0.1849	1800	2.3838
2.384	0.1951	1900	2.3715
2.3625	0.2054	2000	2.3617
2.353	0.2157	2100	2.3717
2.3554	0.2259	2200	2.3543
2.3426	0.2362	2300	2.3422
2.3522	0.2465	2400	2.3428
2.3355	0.2568	2500	2.3437
2.3451	0.2670	2600	2.3227
2.335	0.2773	2700	2.3303
2.3107	0.2876	2800	2.3312
2.3336	0.2978	2900	2.3223
2.3075	0.3081	3000	2.3116
2.2991	0.3184	3100	2.3155
2.3183	0.3286	3200	2.3094
2.3085	0.3389	3300	2.3035
2.3049	0.3492	3400	2.2998
2.3003	0.3595	3500	2.2944
2.3067	0.3697	3600	2.3003
2.2962	0.3800	3700	2.3012
2.2918	0.3903	3800	2.2859
2.2761	0.4005	3900	2.2826
2.2916	0.4108	4000	2.2703
2.2744	0.4211	4100	2.2754
2.2687	0.4313	4200	2.2646
2.2673	0.4416	4300	2.2654
2.2472	0.4519	4400	2.2617
2.2669	0.4622	4500	2.2536
2.2516	0.4724	4600	2.2585
2.2392	0.4827	4700	2.2514
2.2551	0.4930	4800	2.2445
2.2539	0.5032	4900	2.2380
2.2462	0.5135	5000	2.2374
2.2168	0.5238	5100	2.2376
2.2447	0.5340	5200	2.2272
2.2022	0.5443	5300	2.2081
2.2052	0.5546	5400	2.2144
2.213	0.5649	5500	2.2079
2.2078	0.5751	5600	2.2071
2.199	0.5854	5700	2.2007
2.2037	0.5957	5800	2.1961
2.2061	0.6059	5900	2.1962
2.1766	0.6162	6000	2.1861
2.1852	0.6265	6100	2.1868
2.1859	0.6367	6200	2.1777
2.1891	0.6470	6300	2.1753
2.1611	0.6573	6400	2.1712
2.1444	0.6676	6500	2.1659
2.157	0.6778	6600	2.1505
2.1554	0.6881	6700	2.1399
2.1344	0.6984	6800	2.1402
2.1306	0.7086	6900	2.1252
2.0952	0.7189	7000	2.1077
2.0969	0.7292	7100	2.0913
2.1258	0.7394	7200	2.0886
2.0826	0.7497	7300	2.0780
2.0782	0.7600	7400	2.0791
2.0802	0.7703	7500	2.0685
2.0786	0.7805	7600	2.0647
2.0618	0.7908	7700	2.0588
2.0593	0.8011	7800	2.0619
2.0643	0.8113	7900	2.0614
2.057	0.8216	8000	2.0661
2.0588	0.8319	8100	2.0524
2.0686	0.8421	8200	2.0546
2.0333	0.8524	8300	2.0496
2.0621	0.8627	8400	2.0474
2.023	0.8730	8500	2.0390
2.0507	0.8832	8600	2.0414
2.0476	0.8935	8700	2.0421
2.033	0.9038	8800	2.0400
2.0617	0.9140	8900	2.0383
2.0287	0.9243	9000	2.0441
2.0156	0.9346	9100	2.0335
2.0207	0.9448	9200	2.0337
2.036	0.9551	9300	2.0236
2.0411	0.9654	9400	2.0360
2.0277	0.9757	9500	2.0262
2.0449	0.9859	9600	2.0298
2.0323	0.9962	9700	2.0287
2.0124	1.0065	9800	2.0220
2.0211	1.0167	9900	2.0266
2.0137	1.0270	10000	2.0147
2.0169	1.0373	10100	2.0132
2.0075	1.0476	10200	2.0189
2.0022	1.0578	10300	2.0218
2.0172	1.0681	10400	2.0088
2.0152	1.0784	10500	2.0121
1.9993	1.0886	10600	2.0136
2.0109	1.0989	10700	2.0035
2.0155	1.1092	10800	2.0092
2.0101	1.1194	10900	2.0123
2.0028	1.1297	11000	2.0066
2.005	1.1400	11100	2.0060
2.0002	1.1503	11200	2.0026
1.994	1.1605	11300	2.0017
1.9938	1.1708	11400	2.0023
1.9896	1.1811	11500	2.0062
1.9957	1.1913	11600	1.9995
1.987	1.2016	11700	1.9973
2.0086	1.2119	11800	1.9899
1.994	1.2221	11900	1.9962
1.9668	1.2324	12000	1.9951
2.0094	1.2427	12100	1.9944
1.9898	1.2530	12200	1.9907
1.9958	1.2632	12300	1.9728
2.0	1.2735	12400	1.9864
1.9818	1.2838	12500	1.9907
2.0054	1.2940	12600	1.9877
1.9837	1.3043	12700	1.9925
1.9938	1.3146	12800	1.9869
2.0015	1.3248	12900	1.9958
1.9753	1.3351	13000	1.9873
1.9632	1.3454	13100	1.9920
1.9932	1.3557	13200	1.9782
1.9875	1.3659	13300	1.9777
1.9693	1.3762	13400	1.9826
1.9898	1.3865	13500	1.9748
1.9678	1.3967	13600	1.9892
1.989	1.4070	13700	1.9770
1.9789	1.4173	13800	1.9684
1.9733	1.4275	13900	1.9726
1.9623	1.4378	14000	1.9726
1.95	1.4481	14100	1.9733
1.9679	1.4584	14200	1.9689
1.964	1.4686	14300	1.9788
2.0041	1.4789	14400	1.9707
1.9626	1.4892	14500	1.9641
1.979	1.4994	14600	1.9682
1.9558	1.5097	14700	1.9677
1.9701	1.5200	14800	1.9677
1.976	1.5302	14900	1.9659
1.9448	1.5405	15000	1.9627
1.9494	1.5508	15100	1.9698
1.9552	1.5611	15200	1.9746
1.9628	1.5713	15300	1.9635
1.9589	1.5816	15400	1.9668
1.9769	1.5919	15500	1.9625
1.9513	1.6021	15600	1.9599
1.9578	1.6124	15700	1.9638
1.9694	1.6227	15800	1.9612
1.9508	1.6329	15900	1.9642
1.9568	1.6432	16000	1.9583
1.9474	1.6535	16100	1.9610
1.9616	1.6638	16200	1.9591
1.963	1.6740	16300	1.9621
1.9612	1.6843	16400	1.9602
1.959	1.6946	16500	1.9417
1.945	1.7048	16600	1.9535
1.9519	1.7151	16700	1.9553
1.9361	1.7254	16800	1.9538
1.9411	1.7356	16900	1.9450
1.9614	1.7459	17000	1.9579
1.9634	1.7562	17100	1.9546
1.9559	1.7665	17200	1.9501
1.9483	1.7767	17300	1.9491
1.9603	1.7870	17400	1.9529
1.9559	1.7973	17500	1.9495
1.9464	1.8075	17600	1.9491
1.9598	1.8178	17700	1.9499
1.9349	1.8281	17800	1.9512
1.9515	1.8383	17900	1.9454
1.9481	1.8486	18000	1.9423
1.9479	1.8589	18100	1.9486
1.944	1.8692	18200	1.9579
1.9333	1.8794	18300	1.9406
1.9489	1.8897	18400	1.9439
1.9603	1.9000	18500	1.9437
1.9349	1.9102	18600	1.9366
1.9453	1.9205	18700	1.9440
1.9199	1.9308	18800	1.9397
1.9554	1.9410	18900	1.9443
1.9256	1.9513	19000	1.9345
1.9393	1.9616	19100	1.9372
1.9432	1.9719	19200	1.9392
1.935	1.9821	19300	1.9379
1.9252	1.9924	19400	1.9459
1.9378	2.0027	19500	1.9403
1.9326	2.0129	19600	1.9400
1.9272	2.0232	19700	1.9380
1.9368	2.0335	19800	1.9408
1.9318	2.0438	19900	1.9284
1.9165	2.0540	20000	1.9395
1.941	2.0643	20100	1.9335
1.9236	2.0746	20200	1.9384
1.9222	2.0848	20300	1.9318
1.9242	2.0951	20400	1.9293
1.9262	2.1054	20500	1.9298
1.9149	2.1156	20600	1.9291
1.9226	2.1259	20700	1.9338
1.9393	2.1362	20800	1.9306
1.9294	2.1465	20900	1.9358
1.9275	2.1567	21000	1.9345
1.918	2.1670	21100	1.9332
1.9164	2.1773	21200	1.9240
1.9248	2.1875	21300	1.9302
1.9128	2.1978	21400	1.9341
1.9159	2.2081	21500	1.9217
1.934	2.2183	21600	1.9261
1.9258	2.2286	21700	1.9244
1.9034	2.2389	21800	1.9384
1.9023	2.2492	21900	1.9233
1.94	2.2594	22000	1.9232
1.9319	2.2697	22100	1.9289
1.8986	2.2800	22200	1.9191
1.9087	2.2902	22300	1.9196
1.9125	2.3005	22400	1.9235
1.9081	2.3108	22500	1.9103
1.9324	2.3210	22600	1.9249
1.9132	2.3313	22700	1.9210
1.9134	2.3416	22800	1.9273
1.923	2.3519	22900	1.9184
1.9271	2.3621	23000	1.9240
1.9089	2.3724	23100	1.9195
1.9232	2.3827	23200	1.9158
1.9153	2.3929	23300	1.9159
1.9303	2.4032	23400	1.9214
1.9267	2.4135	23500	1.9195
1.9041	2.4237	23600	1.9159
1.9104	2.4340	23700	1.9119
1.9126	2.4443	23800	1.9147
1.9179	2.4546	23900	1.9173
1.8934	2.4648	24000	1.9156
1.9213	2.4751	24100	1.9168
1.9244	2.4854	24200	1.9193
1.9064	2.4956	24300	1.9014
1.8898	2.5059	24400	1.9215
1.9063	2.5162	24500	1.9200
1.9105	2.5264	24600	1.9210
1.916	2.5367	24700	1.9113
1.9099	2.5470	24800	1.9090
1.9051	2.5573	24900	1.9060
1.9177	2.5675	25000	1.9181
1.923	2.5778	25100	1.9144
1.8971	2.5881	25200	1.9079
1.9133	2.5983	25300	1.9068
1.9318	2.6086	25400	1.9089
1.9149	2.6189	25500	1.9109
1.9145	2.6291	25600	1.9076
1.911	2.6394	25700	1.9149
1.8884	2.6497	25800	1.9018
1.8946	2.6600	25900	1.9217
1.9106	2.6702	26000	1.9082
1.906	2.6805	26100	1.9063
1.9026	2.6908	26200	1.9070
1.9088	2.7010	26300	1.9059
1.8938	2.7113	26400	1.9019
1.8964	2.7216	26500	1.9131
1.8947	2.7318	26600	1.9096
1.8906	2.7421	26700	1.9053
1.911	2.7524	26800	1.8969
1.887	2.7627	26900	1.9111
1.8864	2.7729	27000	1.9064
1.9195	2.7832	27100	1.9044
1.9129	2.7935	27200	1.9019
1.8915	2.8037	27300	1.8970
1.9035	2.8140	27400	1.9049
1.8755	2.8243	27500	1.8986
1.8939	2.8345	27600	1.8993
1.895	2.8448	27700	1.8978
1.8744	2.8551	27800	1.9052
1.9178	2.8654	27900	1.9040
1.8916	2.8756	28000	1.8977
1.9226	2.8859	28100	1.9014
1.8772	2.8962	28200	1.8990
1.9011	2.9064	28300	1.8888
1.8891	2.9167	28400	1.8998
1.91	2.9270	28500	1.8976
1.9288	2.9372	28600	1.8976
1.8759	2.9475	28700	1.9000
1.8806	2.9578	28800	1.9029
1.8971	2.9681	28900	1.8981
1.9036	2.9783	29000	1.8944
1.8898	2.9886	29100	1.8983
1.8935	2.9989	29200	1.8930
1.8838	3.0091	29300	1.9015
1.8964	3.0194	29400	1.9020
1.895	3.0297	29500	1.8909
1.8864	3.0400	29600	1.8871
1.89	3.0502	29700	1.8857
1.8846	3.0605	29800	1.8958
1.8983	3.0708	29900	1.8910
1.8917	3.0810	30000	1.8936
1.8913	3.0913	30100	1.8986
1.8559	3.1016	30200	1.9011
1.9041	3.1118	30300	1.8858
1.8752	3.1221	30400	1.8983
1.8813	3.1324	30500	1.8963
1.877	3.1427	30600	1.8924
1.8724	3.1529	30700	1.8895
1.8946	3.1632	30800	1.8942
1.8872	3.1735	30900	1.8940
1.8847	3.1837	31000	1.8931
1.8729	3.1940	31100	1.8850
1.8724	3.2043	31200	1.8911
1.864	3.2145	31300	1.8923
1.8824	3.2248	31400	1.8925
1.9007	3.2351	31500	1.8945
1.8993	3.2454	31600	1.8867
1.8687	3.2556	31700	1.8937
1.8768	3.2659	31800	1.8842
1.8744	3.2762	31900	1.8933
1.8877	3.2864	32000	1.8901
1.8644	3.2967	32100	1.8798
1.8631	3.3070	32200	1.8890
1.8833	3.3172	32300	1.8862
1.8889	3.3275	32400	1.8835
1.8934	3.3378	32500	1.8858
1.8905	3.3481	32600	1.8856
1.8965	3.3583	32700	1.8882
1.8833	3.3686	32800	1.8845
1.9017	3.3789	32900	1.8835
1.8885	3.3891	33000	1.8821
1.8852	3.3994	33100	1.8903
1.8727	3.4097	33200	1.8796
1.8788	3.4199	33300	1.8892
1.8609	3.4302	33400	1.8792
1.9	3.4405	33500	1.8748
1.8731	3.4508	33600	1.8825
1.8753	3.4610	33700	1.8773
1.8651	3.4713	33800	1.8853
1.8757	3.4816	33900	1.8819
1.8939	3.4918	34000	1.8832
1.8939	3.5021	34100	1.8811
1.8719	3.5124	34200	1.8812
1.859	3.5226	34300	1.8834
1.8866	3.5329	34400	1.8762
1.888	3.5432	34500	1.8834
1.8816	3.5535	34600	1.8836
1.8855	3.5637	34700	1.8837
1.8731	3.5740	34800	1.8829
1.9	3.5843	34900	1.8847
1.8767	3.5945	35000	1.8773
1.8847	3.6048	35100	1.8841
1.8716	3.6151	35200	1.8773
1.8746	3.6253	35300	1.8905
1.8672	3.6356	35400	1.8835
1.8825	3.6459	35500	1.8796
1.8711	3.6562	35600	1.8781
1.873	3.6664	35700	1.8787
1.8841	3.6767	35800	1.8774
1.8668	3.6870	35900	1.8827
1.8642	3.6972	36000	1.8804
1.8813	3.7075	36100	1.8761
1.8602	3.7178	36200	1.8772
1.8772	3.7280	36300	1.8859
1.8847	3.7383	36400	1.8792
1.8737	3.7486	36500	1.8823
1.8683	3.7589	36600	1.8812
1.8731	3.7691	36700	1.8808
1.8467	3.7794	36800	1.8828
1.8877	3.7897	36900	1.8820
1.8751	3.7999	37000	1.8840
1.8967	3.8102	37100	1.8824
1.8898	3.8205	37200	1.8747
1.8772	3.8307	37300	1.8736
1.8989	3.8410	37400	1.8733
1.8636	3.8513	37500	1.8791
1.8806	3.8616	37600	1.8731
1.8825	3.8718	37700	1.8811
1.8693	3.8821	37800	1.8753
1.8534	3.8924	37900	1.8731
1.867	3.9026	38000	1.8765
1.876	3.9129	38100	1.8801
1.848	3.9232	38200	1.8709
1.8628	3.9334	38300	1.8739
1.8634	3.9437	38400	1.8734
1.8691	3.9540	38500	1.8747
1.8676	3.9643	38600	1.8748
1.874	3.9745	38700	1.8745
1.8757	3.9848	38800	1.8797
1.8573	3.9951	38900	1.8741
1.8578	4.0053	39000	1.8765
1.8755	4.0156	39100	1.8761
1.885	4.0259	39200	1.8760
1.8647	4.0362	39300	1.8759
1.8642	4.0464	39400	1.8760
1.8838	4.0567	39500	1.8747
1.8632	4.0670	39600	1.8747
1.881	4.0772	39700	1.8758
1.8661	4.0875	39800	1.8699
1.8748	4.0978	39900	1.8723
1.8593	4.1080	40000	1.8688
1.8781	4.1183	40100	1.8698
1.847	4.1286	40200	1.8751
1.8534	4.1389	40300	1.8682
1.856	4.1491	40400	1.8704
1.8735	4.1594	40500	1.8710
1.8586	4.1697	40600	1.8695
1.8466	4.1799	40700	1.8686
1.8594	4.1902	40800	1.8692
1.86	4.2005	40900	1.8674
1.8643	4.2107	41000	1.8693
1.8446	4.2210	41100	1.8685
1.8578	4.2313	41200	1.8710
1.8473	4.2416	41300	1.8716
1.865	4.2518	41400	1.8724
1.848	4.2621	41500	1.8731
1.864	4.2724	41600	1.8684
1.8584	4.2826	41700	1.8753
1.842	4.2929	41800	1.8666
1.8735	4.3032	41900	1.8692
1.8621	4.3134	42000	1.8674
1.8604	4.3237	42100	1.8626
1.8586	4.3340	42200	1.8696
1.8914	4.3443	42300	1.8684
1.8752	4.3545	42400	1.8671
1.8856	4.3648	42500	1.8719
1.8712	4.3751	42600	1.8729
1.8535	4.3853	42700	1.8719
1.8787	4.3956	42800	1.8674
1.8659	4.4059	42900	1.8709
1.8818	4.4161	43000	1.8713
1.8459	4.4264	43100	1.8723
1.8766	4.4367	43200	1.8668
1.8629	4.4470	43300	1.8678
1.8594	4.4572	43400	1.8687
1.8589	4.4675	43500	1.8716
1.8755	4.4778	43600	1.8665
1.8526	4.4880	43700	1.8656
1.8675	4.4983	43800	1.8727
1.8503	4.5086	43900	1.8705
1.8606	4.5188	44000	1.8736
1.8677	4.5291	44100	1.8683
1.8571	4.5394	44200	1.8712
1.8752	4.5497	44300	1.8710
1.8528	4.5599	44400	1.8697
1.8815	4.5702	44500	1.8689
1.8768	4.5805	44600	1.8672
1.8815	4.5907	44700	1.8740
1.8539	4.6010	44800	1.8704
1.8776	4.6113	44900	1.8652
1.8446	4.6215	45000	1.8678
1.8704	4.6318	45100	1.8683
1.8522	4.6421	45200	1.8668
1.8827	4.6524	45300	1.8673
1.851	4.6626	45400	1.8652
1.8577	4.6729	45500	1.8638
1.8581	4.6832	45600	1.8694
1.851	4.6934	45700	1.8675
1.8563	4.7037	45800	1.8704
1.8778	4.7140	45900	1.8656
1.8597	4.7242	46000	1.8676
1.8501	4.7345	46100	1.8684
1.8608	4.7448	46200	1.8684
1.8609	4.7551	46300	1.8687
1.8681	4.7653	46400	1.8649
1.8625	4.7756	46500	1.8672
1.8467	4.7859	46600	1.8681
1.8359	4.7961	46700	1.8669
1.855	4.8064	46800	1.8667
1.8551	4.8167	46900	1.8662
1.8658	4.8269	47000	1.8655
1.8621	4.8372	47100	1.8682
1.8679	4.8475	47200	1.8691
1.8653	4.8578	47300	1.8669
1.8427	4.8680	47400	1.8645
1.8538	4.8783	47500	1.8658
1.8617	4.8886	47600	1.8656
1.8693	4.8988	47700	1.8661
1.8379	4.9091	47800	1.8668
1.8709	4.9194	47900	1.8673
1.8537	4.9296	48000	1.8664
1.8568	4.9399	48100	1.8664
1.867	4.9502	48200	1.8661
1.8591	4.9605	48300	1.8658
1.8565	4.9707	48400	1.8661
1.8541	4.9810	48500	1.8667
1.8736	4.9913	48600	1.8668

Framework versions

PEFT 0.12.0
Transformers 4.43.3
Pytorch 1.13.1+cu117
Datasets 2.19.2
Tokenizers 0.19.1

aryaadhi/Gemma-Medical-QA-LoRA

Gemma-Medical-QA-LoRA

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

aryaadhi/
Gemma-Medical-QA-LoRA