Salesforce-codet5-small-CodeXGLUE-CONCODE-adamw

This model is a fine-tuned version of Salesforce/codet5-small on an unknown dataset. It achieves the following results on the evaluation set:

Model description

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The following hyperparameters were used during training:

Training Loss	Epoch	Step	Validation Loss	Exact Match	Rouge1	Rouge2	Rougel	Rougelsum	Bleu
2.3935	0.16	500	0.9724	0.129	0.5286	0.3466	0.5098	0.5153	0.1127
0.8984	0.32	1000	0.8919	0.138	0.5463	0.3714	0.5285	0.5353	0.1200
0.8121	0.48	1500	0.8583	0.1455	0.5529	0.3787	0.5350	0.5426	0.1158
0.7598	0.64	2000	0.8437	0.1485	0.5541	0.3813	0.5355	0.5432	0.1197
0.7289	0.8	2500	0.8189	0.158	0.5597	0.3906	0.5416	0.5501	0.1222
0.7053	0.96	3000	0.8145	0.161	0.5572	0.3888	0.5392	0.5469	0.1222
0.6544	1.12	3500	0.7982	0.1565	0.5606	0.3920	0.5436	0.5517	0.1260
0.6334	1.28	4000	0.7974	0.1585	0.5633	0.3906	0.5448	0.5529	0.1284
0.6236	1.44	4500	0.7943	0.163	0.5639	0.3931	0.5455	0.5542	0.1275
0.6221	1.6	5000	0.7824	0.1655	0.5718	0.4011	0.5537	0.5621	0.1310
0.608	1.76	5500	0.7792	0.163	0.5664	0.3997	0.5490	0.5567	0.1314
0.5956	1.92	6000	0.7785	0.1605	0.5641	0.3981	0.5470	0.5546	0.1294
0.5701	2.08	6500	0.7800	0.157	0.5673	0.3955	0.5489	0.5568	0.1336
0.5378	2.24	7000	0.7720	0.1655	0.5686	0.4000	0.5504	0.5582	0.1308
0.541	2.4	7500	0.7709	0.1625	0.5699	0.3984	0.5511	0.5590	0.1313
0.5359	2.56	8000	0.7673	0.164	0.5697	0.4023	0.5521	0.5601	0.1332
0.5322	2.72	8500	0.7642	0.1665	0.5708	0.4033	0.5527	0.5606	0.1350
0.5387	2.88	9000	0.7622	0.159	0.5672	0.3988	0.5500	0.5573	0.1342
0.514	3.04	9500	0.7700	0.166	0.5722	0.4052	0.5546	0.5618	0.1352
0.4895	3.2	10000	0.7676	0.1615	0.5696	0.4016	0.5516	0.5591	0.1359
0.4827	3.36	10500	0.7665	0.162	0.5756	0.4072	0.5577	0.5656	0.1367
0.4814	3.52	11000	0.7700	0.1605	0.5709	0.4026	0.5528	0.5605	0.1334
0.4847	3.68	11500	0.7666	0.163	0.5716	0.4046	0.5536	0.5614	0.1335