Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Bert precision	Bert recall	Average word count	Max word count	Min word count	Average token count	% shortened texts with length > 12
1.2656	1.0	16	1.6819	0.5512	0.3185	0.4947	0.4946	0.8804	0.8891	11.8643	18	5	17.0071	45.7143
1.1187	2.0	32	1.5924	0.567	0.3403	0.5157	0.5151	0.8857	0.8954	11.8214	18	3	16.7786	45.7143
1.0753	3.0	48	1.5304	0.5832	0.3555	0.5319	0.5304	0.8881	0.8998	11.9571	18	4	17.0357	46.4286
1.0235	4.0	64	1.4952	0.5785	0.3453	0.5277	0.527	0.8875	0.9003	11.8857	17	6	17.0286	42.8571
0.9861	5.0	80	1.4627	0.5894	0.3606	0.5388	0.5379	0.8885	0.901	11.9429	17	6	17.1929	43.5714
0.9616	6.0	96	1.4499	0.59	0.3567	0.536	0.5355	0.8877	0.9019	12.0071	18	6	17.2714	42.8571
0.9193	7.0	112	1.4335	0.5912	0.3627	0.5427	0.5419	0.8877	0.9025	11.9786	17	6	17.3571	40.7143
0.8959	8.0	128	1.4193	0.5866	0.3583	0.5346	0.5337	0.8887	0.9016	11.7714	17	6	17.1143	38.5714
0.8834	9.0	144	1.4090	0.5979	0.369	0.5469	0.5464	0.8908	0.9042	11.7	16	6	17.2071	37.8571
0.8468	10.0	160	1.4035	0.5977	0.3678	0.5473	0.5469	0.8916	0.9048	11.7643	17	6	17.2071	35.7143
0.8297	11.0	176	1.3956	0.5986	0.365	0.549	0.5475	0.8934	0.9046	11.5857	16	6	16.9429	32.8571
0.8275	12.0	192	1.3934	0.6027	0.3731	0.555	0.5551	0.8934	0.9049	11.6143	17	6	16.9286	32.8571
0.8072	13.0	208	1.3915	0.5973	0.3672	0.5484	0.5472	0.8921	0.905	11.7214	16	6	17.0857	35.7143
0.7744	14.0	224	1.3972	0.6006	0.3707	0.5544	0.5529	0.8947	0.9051	11.5214	16	6	16.8714	33.5714
0.7626	15.0	240	1.3910	0.6039	0.3745	0.5586	0.5576	0.8962	0.9053	11.5071	16	6	16.7071	36.4286
0.7564	16.0	256	1.3918	0.6046	0.3739	0.5571	0.5563	0.8943	0.906	11.7286	17	6	17.0214	40.0
0.7599	17.0	272	1.3822	0.6025	0.3753	0.5549	0.5542	0.8939	0.9059	11.6571	16	6	17.0429	35.7143
0.7331	18.0	288	1.3885	0.6019	0.3705	0.5548	0.5539	0.8935	0.9048	11.65	16	6	17.0357	34.2857
0.7227	19.0	304	1.3916	0.6084	0.3825	0.563	0.5628	0.8991	0.9069	11.2214	16	6	16.5786	27.1429
0.6906	20.0	320	1.4023	0.6065	0.3797	0.5579	0.5579	0.8934	0.9067	11.7714	16	7	17.1357	37.1429
0.6917	21.0	336	1.4052	0.6095	0.3831	0.5621	0.5623	0.8965	0.9072	11.4357	16	6	16.7786	31.4286
0.6867	22.0	352	1.4104	0.6026	0.3807	0.5558	0.5561	0.8928	0.9057	11.5857	16	6	17.0643	31.4286
0.6995	23.0	368	1.4127	0.5999	0.3744	0.5514	0.5511	0.8941	0.9034	11.3571	16	6	16.6714	29.2857
0.6699	24.0	384	1.4217	0.6003	0.3804	0.5558	0.5551	0.8945	0.906	11.4714	16	7	16.8857	29.2857
0.6598	25.0	400	1.4344	0.5975	0.3744	0.552	0.5517	0.8943	0.9053	11.4429	16	6	16.7857	29.2857
0.6592	26.0	416	1.4340	0.6081	0.3868	0.5617	0.5614	0.8964	0.9071	11.3786	16	7	16.8	27.8571
0.6651	27.0	432	1.4375	0.6005	0.3741	0.553	0.553	0.8947	0.9042	11.3714	16	6	16.7071	28.5714
0.6409	28.0	448	1.4511	0.5977	0.3713	0.5508	0.5508	0.8959	0.9033	11.05	16	6	16.45	22.1429
0.6373	29.0	464	1.4670	0.5918	0.3655	0.5426	0.5426	0.8933	0.9026	11.3429	16	7	16.8071	25.7143
0.6284	30.0	480	1.4591	0.5973	0.3782	0.5497	0.5498	0.8947	0.904	11.3	16	7	16.8	24.2857
0.6214	31.0	496	1.4709	0.5987	0.3806	0.5543	0.5543	0.8963	0.9041	11.2214	16	6	16.6714	25.7143
0.6086	32.0	512	1.4839	0.5874	0.3667	0.5442	0.5434	0.8942	0.9016	11.1357	16	6	16.5429	26.4286
0.6102	33.0	528	1.4852	0.5928	0.3746	0.5479	0.5474	0.8954	0.9022	11.1286	16	6	16.5071	24.2857
0.6118	34.0	544	1.4869	0.5962	0.3766	0.5488	0.5486	0.8948	0.9035	11.4	16	7	16.7643	27.1429
0.605	35.0	560	1.4881	0.5943	0.3746	0.5461	0.5457	0.8942	0.9019	11.3143	16	7	16.7929	26.4286
0.6039	36.0	576	1.4854	0.5903	0.3716	0.5431	0.5431	0.8957	0.9014	11.1	16	7	16.45	24.2857
0.5777	37.0	592	1.4901	0.5922	0.3685	0.5461	0.546	0.8943	0.9042	11.3786	16	7	16.8143	26.4286
0.5634	38.0	608	1.4975	0.594	0.3721	0.5454	0.5446	0.8958	0.9019	11.0929	16	7	16.4286	22.8571
0.5794	39.0	624	1.5088	0.5963	0.3792	0.5515	0.5508	0.896	0.9026	11.2429	16	7	16.55	24.2857
0.5825	40.0	640	1.5150	0.5951	0.3736	0.5512	0.5502	0.895	0.9031	11.3786	16	6	16.6643	27.8571
0.5632	41.0	656	1.5230	0.5998	0.3731	0.5571	0.5561	0.9	0.9037	11.0714	16	6	16.1214	22.1429
0.5544	42.0	672	1.5356	0.6036	0.3798	0.5628	0.5628	0.8987	0.9046	11.2143	16	7	16.3143	22.8571
0.5672	43.0	688	1.5493	0.5944	0.3671	0.5502	0.5504	0.8954	0.9024	11.3786	16	7	16.6	25.0
0.551	44.0	704	1.5563	0.5859	0.362	0.543	0.5426	0.8957	0.9002	11.1214	15	7	16.35	23.5714
0.543	45.0	720	1.5601	0.592	0.3643	0.5484	0.5481	0.8968	0.9014	11.0929	17	7	16.3	22.8571
0.5352	46.0	736	1.5680	0.6039	0.3783	0.5618	0.5614	0.8987	0.905	11.1929	17	7	16.4071	23.5714
0.528	47.0	752	1.5732	0.595	0.3721	0.5562	0.5558	0.8968	0.9024	11.1643	17	7	16.3714	25.0
0.528	48.0	768	1.5749	0.5933	0.372	0.5539	0.5537	0.896	0.9026	11.2643	17	7	16.4857	25.7143
0.5296	49.0	784	1.5795	0.596	0.3726	0.554	0.5541	0.897	0.904	11.2571	17	7	16.4571	26.4286
0.5235	50.0	800	1.5828	0.5916	0.3679	0.5484	0.548	0.8951	0.9019	11.2643	17	7	16.4571	27.1429
0.5168	51.0	816	1.5879	0.5917	0.368	0.5473	0.5465	0.8962	0.9006	11.1857	17	7	16.2286	25.7143
0.5133	52.0	832	1.5932	0.5928	0.3665	0.5473	0.5465	0.8979	0.9018	11.1643	17	7	16.2643	21.4286
0.5036	53.0	848	1.6016	0.5927	0.3703	0.5508	0.5511	0.8949	0.9012	11.3286	17	7	16.4143	26.4286
0.492	54.0	864	1.6074	0.5922	0.37	0.5496	0.5493	0.8953	0.9021	11.3643	17	7	16.5214	26.4286
0.5184	55.0	880	1.6153	0.5953	0.3714	0.5542	0.5536	0.8963	0.9027	11.3	17	7	16.5	24.2857
0.5057	56.0	896	1.6311	0.5874	0.3636	0.5424	0.5425	0.896	0.9009	11.0857	17	7	16.2429	21.4286
0.5053	57.0	912	1.6356	0.5835	0.3623	0.5411	0.5408	0.8953	0.8996	11.1929	17	7	16.3143	25.7143
0.5016	58.0	928	1.6342	0.5908	0.3679	0.5475	0.5472	0.8966	0.9011	11.1214	17	7	16.2929	23.5714
0.4921	59.0	944	1.6312	0.5899	0.3719	0.5495	0.549	0.8966	0.9006	11.0429	17	7	16.1929	25.0
0.5051	60.0	960	1.6316	0.5989	0.3766	0.5572	0.5566	0.8964	0.9045	11.3214	17	7	16.6643	25.7143
0.4938	61.0	976	1.6377	0.6007	0.3812	0.5581	0.5578	0.898	0.903	11.1214	17	7	16.2357	25.0
0.4843	62.0	992	1.6437	0.5981	0.3844	0.5597	0.5595	0.8965	0.9033	11.1714	17	7	16.3286	26.4286
0.4894	63.0	1008	1.6473	0.594	0.3718	0.5525	0.5523	0.8951	0.903	11.2857	17	7	16.5071	28.5714
0.4956	64.0	1024	1.6549	0.5843	0.37	0.5449	0.5447	0.895	0.8995	11.0929	17	7	16.2	25.7143
0.4852	65.0	1040	1.6543	0.5947	0.3742	0.5553	0.555	0.8958	0.9024	11.35	17	7	16.55	27.8571
0.489	66.0	1056	1.6558	0.5922	0.3751	0.5546	0.5544	0.896	0.9014	11.1357	17	7	16.2857	25.7143
0.4852	67.0	1072	1.6619	0.591	0.376	0.5522	0.5523	0.8959	0.9016	11.1571	17	7	16.2571	23.5714
0.4847	68.0	1088	1.6699	0.5913	0.3781	0.556	0.5556	0.8969	0.901	11.0214	17	7	16.1357	22.8571
0.4685	69.0	1104	1.6720	0.5909	0.3755	0.5516	0.5517	0.8961	0.9015	11.2571	17	7	16.35	25.0
0.4799	70.0	1120	1.6734	0.586	0.3654	0.5448	0.5454	0.8937	0.8998	11.25	17	7	16.3214	24.2857
0.4781	71.0	1136	1.6765	0.5844	0.3634	0.5429	0.5428	0.8927	0.8996	11.35	17	7	16.4929	26.4286
0.4843	72.0	1152	1.6814	0.5864	0.3619	0.5426	0.5432	0.8928	0.9006	11.4286	17	7	16.5929	27.8571
0.4658	73.0	1168	1.6846	0.5888	0.3628	0.5431	0.5437	0.8941	0.9001	11.3214	17	7	16.4429	25.7143
0.4664	74.0	1184	1.6899	0.5885	0.3692	0.5473	0.5473	0.8949	0.9	11.1786	17	7	16.3143	22.1429
0.4805	75.0	1200	1.6954	0.5915	0.3765	0.5506	0.5511	0.8956	0.9013	11.2286	17	7	16.3643	23.5714
0.4708	76.0	1216	1.6964	0.5888	0.37	0.5479	0.5483	0.8964	0.9004	11.0571	17	7	16.1929	21.4286
0.4483	77.0	1232	1.6968	0.5881	0.3669	0.5455	0.5457	0.8954	0.8999	11.1214	17	7	16.2857	22.8571
0.4699	78.0	1248	1.6993	0.5908	0.369	0.5477	0.5481	0.8957	0.9015	11.1786	15	7	16.3857	24.2857
0.4657	79.0	1264	1.7014	0.5927	0.3734	0.5528	0.553	0.8971	0.9021	11.1429	15	7	16.3214	22.8571
0.4616	80.0	1280	1.7063	0.5919	0.3743	0.5531	0.5533	0.8975	0.9009	11.0714	15	7	16.25	20.7143
0.4706	81.0	1296	1.7087	0.5933	0.3728	0.5521	0.5525	0.8976	0.9015	11.0643	15	7	16.2429	21.4286
0.4557	82.0	1312	1.7109	0.5917	0.3717	0.5517	0.5515	0.8971	0.902	11.1429	17	7	16.35	22.8571
0.474	83.0	1328	1.7164	0.5918	0.3714	0.5507	0.5509	0.8967	0.9024	11.2357	17	7	16.4143	24.2857
0.4715	84.0	1344	1.7165	0.591	0.3717	0.5522	0.5533	0.8975	0.9025	11.1071	17	7	16.2857	22.8571
0.462	85.0	1360	1.7159	0.5892	0.3708	0.5479	0.5481	0.896	0.9021	11.2071	17	7	16.3714	23.5714
0.455	86.0	1376	1.7171	0.5943	0.379	0.5551	0.5559	0.898	0.9031	11.1929	17	7	16.3429	23.5714
0.4613	87.0	1392	1.7173	0.5894	0.371	0.5501	0.5507	0.8967	0.9018	11.2	17	7	16.3571	22.8571
0.4663	88.0	1408	1.7191	0.5895	0.3705	0.5505	0.5509	0.8968	0.9018	11.1857	17	7	16.3429	22.1429
0.4662	89.0	1424	1.7213	0.5893	0.3692	0.5498	0.5501	0.8961	0.9012	11.2214	17	7	16.3714	23.5714
0.4352	90.0	1440	1.7202	0.5886	0.3696	0.549	0.5498	0.8963	0.9015	11.2214	17	7	16.3714	23.5714
0.4567	91.0	1456	1.7193	0.5885	0.373	0.5509	0.5516	0.8968	0.9022	11.1929	17	7	16.3429	23.5714
0.4421	92.0	1472	1.7211	0.5885	0.3734	0.5498	0.5505	0.8962	0.9022	11.2429	17	7	16.3857	24.2857
0.4655	93.0	1488	1.7230	0.5925	0.3763	0.5537	0.5538	0.8977	0.9029	11.1929	17	7	16.35	23.5714
0.4431	94.0	1504	1.7246	0.5912	0.3765	0.5529	0.5531	0.898	0.903	11.1929	17	7	16.3286	22.8571
0.4493	95.0	1520	1.7258	0.5921	0.3756	0.5531	0.5535	0.8979	0.903	11.2357	17	7	16.3714	22.8571
0.4546	96.0	1536	1.7272	0.5918	0.375	0.5529	0.5533	0.8978	0.9029	11.2357	17	7	16.3643	23.5714
0.4558	97.0	1552	1.7279	0.5925	0.3744	0.5536	0.554	0.8979	0.9029	11.2071	17	7	16.3357	22.8571
0.4575	98.0	1568	1.7281	0.592	0.3746	0.5532	0.5533	0.8978	0.9029	11.2	17	7	16.3357	22.8571
0.441	99.0	1584	1.7285	0.5919	0.3742	0.5529	0.5532	0.8978	0.9029	11.1929	17	7	16.3286	22.1429
0.4529	100.0	1600	1.7285	0.5919	0.3742	0.5529	0.5532	0.8979	0.9029	11.1929	17	7	16.3286	22.1429

Framework versions

Transformers 4.32.1
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3

ldos/text_shortening_model_v9

text_shortening_model_v9

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

ldos/
text_shortening_model_v9