Training Loss	Epoch	Step	Validation Loss	Accuracy	F1 Macro	F1 Class 0	F1 Class 1	F1 Class 2	F1 Class 3	F1 Class 4	F1 Class 5	F1 Class 6	F1 Class 7	F1 Class 8
1.3064	0.25	250	0.7912	0.7411	0.5153	0.9353	0.0	0.5769	0.0	0.5222	0.8352	0.8477	0.9206	0.0
0.7377	0.5	500	0.6851	0.8024	0.6114	0.9458	0.0	0.6388	0.6040	0.6406	0.8646	0.8772	0.9313	0.0
0.5968	0.75	750	0.5917	0.8421	0.6460	0.9474	0.0	0.7722	0.7052	0.6909	0.8887	0.8812	0.9281	0.0
0.5028	1.01	1000	0.5893	0.8502	0.6523	0.9476	0.0	0.7700	0.7263	0.7564	0.8674	0.8537	0.9497	0.0
0.4657	1.26	1250	0.5319	0.8663	0.6671	0.9493	0.0	0.7830	0.7870	0.7650	0.8965	0.8777	0.9457	0.0
0.4047	1.51	1500	0.5214	0.8708	0.7452	0.9492	0.0	0.8141	0.7774	0.7784	0.8755	0.8978	0.9477	0.6667
0.4021	1.76	1750	0.5208	0.8773	0.7344	0.9476	0.0	0.7609	0.7879	0.8015	0.9156	0.8945	0.9563	0.5455
0.4	2.01	2000	0.4734	0.8879	0.8306	0.9527	0.6667	0.8274	0.8047	0.7965	0.9217	0.8856	0.9531	0.6667
0.2616	2.26	2250	0.5733	0.8763	0.7283	0.9577	0.0	0.7973	0.7926	0.8100	0.9012	0.8978	0.9278	0.4706
0.3004	2.52	2500	0.5050	0.8934	0.7959	0.9672	0.3333	0.8480	0.8235	0.8051	0.9149	0.8903	0.9556	0.625
0.3136	2.77	2750	0.4735	0.8894	0.8483	0.9511	0.9091	0.8444	0.7893	0.7992	0.9186	0.9	0.9514	0.5714
0.3091	3.02	3000	0.4670	0.8904	0.8349	0.9526	0.6667	0.8398	0.8278	0.8050	0.9111	0.8943	0.9504	0.6667
0.1983	3.27	3250	0.5770	0.8914	0.8328	0.9551	0.7500	0.8478	0.7956	0.8120	0.9156	0.8884	0.9598	0.5714
0.1782	3.52	3500	0.5193	0.8974	0.8245	0.9511	0.5714	0.8410	0.8353	0.8225	0.9196	0.9123	0.9521	0.6154
0.2419	3.77	3750	0.4857	0.8949	0.8129	0.9567	0.5	0.8495	0.7988	0.8177	0.9209	0.8980	0.9587	0.6154
0.2209	4.02	4000	0.5167	0.8994	0.7900	0.9501	0.3333	0.8509	0.8134	0.8345	0.9215	0.9112	0.9621	0.5333
0.1367	4.28	4250	0.6125	0.8919	0.8537	0.9582	0.8889	0.8411	0.8144	0.8190	0.9066	0.8820	0.9580	0.6154
0.1523	4.53	4500	0.5453	0.8944	0.8287	0.9565	0.7500	0.8404	0.8249	0.8155	0.9147	0.9002	0.9561	0.5
0.1666	4.78	4750	0.5185	0.9025	0.8497	0.9713	0.6667	0.8392	0.8394	0.8306	0.9226	0.9027	0.9601	0.7143
0.1388	5.03	5000	0.5815	0.8934	0.7865	0.9583	0.3333	0.8462	0.8288	0.8217	0.9126	0.8908	0.9604	0.5263
0.1039	5.28	5250	0.6477	0.8929	0.8184	0.9533	0.5	0.8431	0.8239	0.8103	0.9150	0.8913	0.9616	0.6667
0.0942	5.53	5500	0.6873	0.8864	0.8112	0.9603	0.6667	0.8424	0.8033	0.8031	0.9017	0.8914	0.9559	0.4762
0.1063	5.78	5750	0.6684	0.8944	0.8325	0.9675	0.5714	0.8557	0.8120	0.8204	0.9082	0.8884	0.9547	0.7143
0.0945	6.04	6000	0.6209	0.8939	0.8183	0.9654	0.5714	0.8537	0.8184	0.8112	0.9175	0.8982	0.9405	0.5882
0.0771	6.29	6250	0.6268	0.8994	0.8563	0.9638	0.7500	0.8398	0.8363	0.8373	0.9123	0.8924	0.9605	0.7143
0.0845	6.54	6500	0.6382	0.8939	0.8417	0.9692	0.7500	0.8429	0.8179	0.8151	0.9123	0.8884	0.9548	0.625
0.0673	6.79	6750	0.6561	0.9010	0.8315	0.9693	0.5714	0.8404	0.8214	0.8342	0.9252	0.8928	0.9616	0.6667
0.0641	7.04	7000	0.7066	0.8879	0.8407	0.9617	0.7500	0.8467	0.7923	0.8107	0.9077	0.8795	0.9512	0.6667
0.039	7.29	7250	0.6932	0.8949	0.8459	0.9659	0.7500	0.8510	0.8079	0.8178	0.9185	0.8767	0.9590	0.6667
0.0372	7.55	7500	0.6786	0.8984	0.8705	0.9658	0.8889	0.8626	0.8232	0.8194	0.9134	0.8859	0.9607	0.7143
0.0504	7.8	7750	0.6914	0.8949	0.8598	0.9641	0.9091	0.8478	0.8202	0.8104	0.9177	0.8874	0.9561	0.625
0.0409	8.05	8000	0.7027	0.8984	0.8501	0.9658	0.7500	0.8475	0.8387	0.8195	0.9142	0.8879	0.9607	0.6667
0.0196	8.3	8250	0.7222	0.8969	0.8530	0.9659	0.7500	0.8492	0.8202	0.8123	0.9184	0.8849	0.9621	0.7143
0.0323	8.55	8500	0.6858	0.8999	0.8551	0.9697	0.8889	0.8606	0.8235	0.8218	0.9181	0.9015	0.9561	0.5556
0.0274	8.8	8750	0.6813	0.9010	0.8557	0.9660	0.8889	0.8517	0.8300	0.8270	0.9186	0.9015	0.9618	0.5556
0.0212	9.05	9000	0.7197	0.8979	0.8608	0.9677	0.8889	0.8456	0.8272	0.8281	0.9111	0.8899	0.9633	0.625
0.0065	9.31	9250	0.7363	0.8979	0.8601	0.9696	0.8889	0.8463	0.8199	0.8220	0.9152	0.8924	0.9618	0.625
0.0115	9.56	9500	0.7331	0.8974	0.8647	0.9677	0.8889	0.8504	0.8249	0.8204	0.9105	0.8909	0.9619	0.6667
0.0059	9.81	9750	0.7349	0.8989	0.8660	0.9695	0.8889	0.8462	0.8319	0.8226	0.9121	0.8953	0.9606	0.6667

Framework versions

Transformers 4.32.1
Pytorch 2.0.1+cu117
Datasets 2.14.4
Tokenizers 0.13.3

bendico765/DuplicatiDistillBertFullTraining

DuplicatiDistillBertFullTraining

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

bendico765/
DuplicatiDistillBertFullTraining