mt5-base-b8-e16-t58k-jupyter

This model is a fine-tuned version of google/mt5-base on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.2383
• Rouge1: 67.8581
• Rouge2: 59.4302
• Rougel: 67.7221
• Rougelsum: 67.6929
• Gen Len: 19.1351

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: 0.001
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Use OptimizerNames.ADAFACTOR and the args are: No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 16

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
0.8846	0.1379	1000	0.4117	58.1956	47.2104	57.8222	57.8168	19.0252
0.506	0.2759	2000	0.3460	59.4398	49.0483	59.2127	59.2088	18.9282
0.4479	0.4138	3000	0.3214	64.1438	54.2258	63.8836	63.8605	19.1916
0.3963	0.5517	4000	0.2981	65.6803	56.0098	65.4391	65.4087	19.1486
0.3771	0.6897	5000	0.2828	67.1769	57.8865	66.9535	66.9212	19.1732
0.3478	0.8276	6000	0.2723	67.2249	58.1005	67.0126	66.9823	19.1721
0.3332	0.9655	7000	0.2563	67.6065	58.7448	67.4238	67.3956	19.1829
0.2553	1.1034	8000	0.2752	66.6302	57.9725	66.4682	66.4449	19.1119
0.2396	1.2414	9000	0.2604	67.9608	59.219	67.7935	67.76	19.1086
0.2369	1.3793	10000	0.2555	68.1951	59.7011	68.0417	68.0072	19.1754
0.2294	1.5172	11000	0.2508	68.0577	59.5206	67.8871	67.8552	19.1344
0.2265	1.6552	12000	0.2424	67.4119	58.7834	67.1999	67.1837	19.1054
0.2228	1.7931	13000	0.2383	67.8581	59.4302	67.7221	67.6929	19.1351
0.2216	1.9310	14000	0.2391	69.1897	61.0788	69.0352	69.0068	19.1914
0.1769	2.0690	15000	0.2494	69.458	61.4372	69.3297	69.3115	19.1916
0.153	2.2069	16000	0.2477	69.357	61.455	69.2285	69.1898	19.1746
0.1512	2.3448	17000	0.2619	68.6959	60.5759	68.5428	68.5083	19.1279
0.1522	2.4828	18000	0.2530	69.2438	61.3816	69.1173	69.0815	19.1781
0.1563	2.6207	19000	0.2466	68.6796	60.6531	68.5412	68.4936	19.1156
0.1507	2.7586	20000	0.2508	69.8035	61.9634	69.683	69.6408	19.1696
0.1533	2.8966	21000	0.2517	70.4486	62.8697	70.3275	70.2894	19.1685
0.1369	3.0345	22000	0.2619	70.0921	62.4997	69.979	69.9386	19.1621
0.1007	3.1724	23000	0.2644	69.8367	62.0731	69.7019	69.6681	19.1614
0.104	3.3103	24000	0.2652	69.9394	62.3593	69.8122	69.7678	19.1571
0.1068	3.4483	25000	0.2655	70.1364	62.553	70.0215	69.9713	19.1851
0.1106	3.5862	26000	0.2591	69.9154	62.1538	69.7887	69.7509	19.1754
0.1085	3.7241	27000	0.2687	70.1055	62.5805	69.9928	69.9442	19.1585
0.1099	3.8621	28000	0.2568	69.7394	61.9854	69.6332	69.5986	19.1552
0.1087	4.0	29000	0.2615	70.1983	62.6796	70.0887	70.058	19.1558
0.0686	4.1379	30000	0.2742	69.0479	61.407	68.9306	68.9027	19.1205
0.0746	4.2759	31000	0.2689	70.4406	62.9053	70.3163	70.2855	19.1558
0.0758	4.4138	32000	0.2777	70.3994	62.855	70.287	70.2398	19.163
0.0772	4.5517	33000	0.2726	70.2671	62.757	70.1461	70.1029	19.1535
0.0788	4.6897	34000	0.2770	69.5882	61.8849	69.4835	69.4429	19.1656
0.0797	4.8276	35000	0.2764	69.9145	62.404	69.789	69.7598	19.1639
0.079	4.9655	36000	0.2747	69.4204	61.8999	69.3158	69.2775	19.1845
0.0587	5.1034	37000	0.2895	70.3877	63.0522	70.2784	70.235	19.1519
0.0527	5.2414	38000	0.2862	69.4405	61.8645	69.3228	69.28	19.1638
0.0533	5.3793	39000	0.2888	69.3483	61.8568	69.2428	69.2095	19.1431
0.0545	5.5172	40000	0.2946	68.2516	60.621	68.1208	68.0861	19.1365
0.0572	5.6552	41000	0.3024	69.4355	61.9683	69.3316	69.2974	19.1386
0.0592	5.7931	42000	0.2909	69.2934	61.6953	69.181	69.1549	19.158
0.06	5.9310	43000	0.2912	68.983	61.4127	68.8525	68.8369	19.1446
0.0473	6.0690	44000	0.3238	70.1649	62.7399	70.0521	70.0103	19.1725
0.0377	6.2069	45000	0.2999	67.2192	59.4114	67.0974	67.0716	19.1046
0.0407	6.3448	46000	0.3181	67.2047	59.6483	67.0705	67.046	19.2064
0.0404	6.4828	47000	0.3069	67.5288	60.02	67.424	67.3754	19.1977
0.0431	6.6207	48000	0.3144	69.8076	62.3682	69.6792	69.6511	19.1865
0.0427	6.7586	49000	0.3154	69.2514	61.7694	69.1338	69.098	19.2413
0.0438	6.8966	50000	0.3042	69.8743	62.4372	69.7374	69.6987	19.1699
0.0395	7.0345	51000	0.3258	70.7026	63.616	70.6003	70.5601	19.184
0.0284	7.1724	52000	0.3281	70.2281	62.9315	70.1089	70.0755	19.1556
0.0295	7.3103	53000	0.3351	70.5253	63.3491	70.4193	70.3758	19.1659
0.0296	7.4483	54000	0.3382	70.799	63.6006	70.6772	70.6426	19.1755
0.0309	7.5862	55000	0.3292	69.4402	62.1832	69.3146	69.2855	19.18
0.0309	7.7241	56000	0.3358	70.628	63.4921	70.5047	70.4596	19.1676
0.0301	7.8621	57000	0.3433	70.4413	63.2207	70.3199	70.2882	19.1719
0.032	8.0	58000	0.3228	70.5812	63.4071	70.4684	70.4319	19.1773
0.0209	8.1379	59000	0.3496	70.4711	63.1854	70.3596	70.3184	19.1645
0.0201	8.2759	60000	0.3559	70.454	63.2365	70.3396	70.3065	19.18
0.0216	8.4138	61000	0.3452	70.7055	63.551	70.5961	70.5624	19.1603
0.0224	8.5517	62000	0.3425	70.6933	63.5627	70.5959	70.5621	19.1645
0.0228	8.6897	63000	0.3489	70.329	63.2136	70.2368	70.1908	19.1737
0.0231	8.8276	64000	0.3502	70.5163	63.3691	70.4183	70.3802	19.1631
0.0226	8.9655	65000	0.3495	70.3915	63.1873	70.2895	70.2553	19.1594
0.0177	9.1034	66000	0.3665	70.3584	63.2121	70.264	70.2218	19.1728
0.0155	9.2414	67000	0.3668	70.4038	63.2343	70.3021	70.2646	19.1545
0.0156	9.3793	68000	0.3858	70.5827	63.3876	70.4804	70.4326	19.1588
0.0164	9.5172	69000	0.3644	70.9777	63.9787	70.8733	70.8334	19.1545
0.0169	9.6552	70000	0.3693	70.7079	63.6767	70.6034	70.5633	19.1623
0.0169	9.7931	71000	0.3734	70.5823	63.4672	70.4804	70.4471	19.1618
0.0179	9.9310	72000	0.3649	70.6698	63.6145	70.5783	70.5333	19.157
0.0135	10.0690	73000	0.3920	70.6779	63.708	70.5869	70.5515	19.1776
0.011	10.2069	74000	0.3957	70.698	63.5898	70.5937	70.5593	19.1579
0.0112	10.3448	75000	0.3880	70.7058	63.6789	70.6075	70.5706	19.169
0.0124	10.4828	76000	0.3868	70.8377	63.8888	70.7722	70.7271	19.1614
0.0117	10.6207	77000	0.3835	70.225	63.1845	70.1412	70.103	19.1719
0.0118	10.7586	78000	0.3999	70.2805	63.1728	70.1672	70.1469	19.1835
0.0118	10.8966	79000	0.3967	69.99	62.9694	69.9026	69.8748	19.1981
0.0104	11.0345	80000	0.4053	70.2508	63.3003	70.1657	70.1329	19.2093
0.0084	11.1724	81000	0.4122	70.0517	63.0268	69.9457	69.9151	19.1805
0.0086	11.3103	82000	0.4025	70.0812	63.1975	69.9947	69.9587	19.1872
0.0082	11.4483	83000	0.4236	70.7138	63.7789	70.6047	70.5832	19.186
0.0082	11.5862	84000	0.4277	70.336	63.4501	70.2562	70.2147	19.177
0.0081	11.7241	85000	0.4084	69.918	62.8952	69.827	69.7926	19.1648
0.0085	11.8621	86000	0.4193	70.4653	63.5381	70.3767	70.3355	19.1803
0.0078	12.0	87000	0.4321	69.7744	62.7571	69.6712	69.6459	19.1737
0.0054	12.1379	88000	0.4411	69.9454	62.9937	69.8503	69.8164	19.1717
0.0056	12.2759	89000	0.4416	70.563	63.6044	70.4674	70.4182	19.1784
0.0058	12.4138	90000	0.4375	69.9383	62.9516	69.8393	69.8138	19.191
0.0057	12.5517	91000	0.4402	69.9012	62.9782	69.7933	69.7575	19.1724
0.005	12.6897	92000	0.4438	69.4525	62.4818	69.357	69.3203	19.1685
0.0058	12.8276	93000	0.4474	70.2012	63.2868	70.1103	70.0678	19.1769
0.0051	12.9655	94000	0.4434	69.8342	62.9167	69.7348	69.704	19.178
0.0045	13.1034	95000	0.4649	69.9998	63.0079	69.9039	69.8638	19.1893
0.0038	13.2414	96000	0.4640	70.2866	63.3656	70.1951	70.1636	19.1724
0.0039	13.3793	97000	0.4702	70.3794	63.5196	70.2901	70.2546	19.1814
0.0042	13.5172	98000	0.4718	70.6757	63.8287	70.5752	70.5308	19.1701
0.0039	13.6552	99000	0.4816	70.4003	63.5464	70.3017	70.267	19.1517
0.0037	13.7931	100000	0.4718	70.3157	63.4538	70.2295	70.1942	19.1746
0.0039	13.9310	101000	0.4643	70.5475	63.6863	70.4635	70.4256	19.1876
0.0031	14.0690	102000	0.4908	70.3373	63.4716	70.2509	70.2061	19.174
0.0028	14.2069	103000	0.4915	70.5516	63.6897	70.4538	70.4149	19.1822
0.0027	14.3448	104000	0.5110	70.5811	63.7133	70.4927	70.4498	19.1751
0.0025	14.4828	105000	0.4974	70.3384	63.4383	70.2609	70.2126	19.1769
0.0026	14.6207	106000	0.5010	70.7552	63.91	70.6802	70.6254	19.1729
0.0029	14.7586	107000	0.4989	70.78	63.9408	70.6996	70.6527	19.1654
0.0023	14.8966	108000	0.5118	70.8186	64.0192	70.7348	70.691	19.1702
0.0028	15.0345	109000	0.5058	70.8076	63.9936	70.7282	70.6829	19.1612
0.0021	15.1724	110000	0.5094	70.5992	63.7622	70.5161	70.4735	19.1668
0.002	15.3103	111000	0.5148	70.6299	63.8373	70.5413	70.4962	19.1736
0.002	15.4483	112000	0.5197	70.6815	63.9035	70.5942	70.5562	19.1678
0.0018	15.5862	113000	0.5218	70.6869	63.9007	70.606	70.5618	19.1734
0.0019	15.7241	114000	0.5232	70.6718	63.8988	70.5768	70.5393	19.1671
0.0019	15.8621	115000	0.5242	70.6659	63.9002	70.5822	70.5401	19.1739
0.0021	16.0	116000	0.5243	70.6792	63.9083	70.5913	70.5479	19.1747

Framework versions

• Transformers 4.49.0
• Pytorch 2.6.0+cu124
• Datasets 3.4.1
• Tokenizers 0.21.1