t5-small-finetuned-text2log-finetuned-nl-to-fol-finetuned-nl-to-fol

This model is a fine-tuned version of anki08/t5-small-finetuned-text2log-finetuned-nl-to-fol on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0117
• Bleu: 26.9533
• Gen Len: 18.7206

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: 5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 200
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Bleu	Gen Len
No log	1.0	17	0.6271	21.6075	18.6912
No log	2.0	34	0.4985	21.6117	18.6912
No log	3.0	51	0.4213	22.1637	18.6912
No log	4.0	68	0.3745	22.4107	18.6912
No log	5.0	85	0.3410	22.8843	18.6912
No log	6.0	102	0.3200	22.8262	18.6912
No log	7.0	119	0.2925	22.6535	18.6912
No log	8.0	136	0.2790	22.733	18.6912
No log	9.0	153	0.2696	23.0984	18.6912
No log	10.0	170	0.2550	22.7433	18.6912
No log	11.0	187	0.2449	22.959	18.6912
No log	12.0	204	0.2301	23.2707	18.6912
No log	13.0	221	0.2222	23.1237	18.6912
No log	14.0	238	0.2098	23.2703	18.6912
No log	15.0	255	0.2010	23.406	18.6912
No log	16.0	272	0.1926	23.5024	18.6912
No log	17.0	289	0.1871	23.644	18.6912
No log	18.0	306	0.1801	23.8176	18.6912
No log	19.0	323	0.1714	23.5624	18.6912
No log	20.0	340	0.1640	23.8308	18.6912
No log	21.0	357	0.1582	23.7387	18.6912
No log	22.0	374	0.1532	23.4223	18.6912
No log	23.0	391	0.1493	23.4963	18.6912
No log	24.0	408	0.1469	23.4319	18.6912
No log	25.0	425	0.1408	23.7634	18.6912
No log	26.0	442	0.1367	23.6347	18.6912
No log	27.0	459	0.1316	23.6694	18.6912
No log	28.0	476	0.1274	23.9273	18.6912
No log	29.0	493	0.1237	24.0772	18.6912
0.3817	30.0	510	0.1190	24.3082	18.6912
0.3817	31.0	527	0.1172	24.4804	18.6691
0.3817	32.0	544	0.1137	24.2785	18.6691
0.3817	33.0	561	0.1107	24.2177	18.6912
0.3817	34.0	578	0.1060	23.6294	18.6912
0.3817	35.0	595	0.1019	24.2786	18.6912
0.3817	36.0	612	0.0991	24.4832	18.6691
0.3817	37.0	629	0.0976	24.7323	18.6691
0.3817	38.0	646	0.0966	24.5546	18.6691
0.3817	39.0	663	0.0951	24.6238	18.6691
0.3817	40.0	680	0.0918	24.4027	18.6691
0.3817	41.0	697	0.0892	24.5354	18.6691
0.3817	42.0	714	0.0866	24.427	18.6691
0.3817	43.0	731	0.0851	24.0645	18.6691
0.3817	44.0	748	0.0836	24.2317	18.6691
0.3817	45.0	765	0.0816	24.4578	18.6691
0.3817	46.0	782	0.0799	24.5216	18.6691
0.3817	47.0	799	0.0774	24.7976	18.6691
0.3817	48.0	816	0.0755	24.6819	18.6691
0.3817	49.0	833	0.0725	24.7607	18.6691
0.3817	50.0	850	0.0720	24.9414	18.6691
0.3817	51.0	867	0.0708	24.6746	18.6691
0.3817	52.0	884	0.0694	24.791	18.6691
0.3817	53.0	901	0.0667	24.7417	18.6691
0.3817	54.0	918	0.0657	24.8431	18.6691
0.3817	55.0	935	0.0645	25.0305	18.6691
0.3817	56.0	952	0.0639	24.986	18.6691
0.3817	57.0	969	0.0615	24.986	18.6691
0.3817	58.0	986	0.0603	25.0536	18.6691
0.2006	59.0	1003	0.0587	25.014	18.6691
0.2006	60.0	1020	0.0576	25.0981	18.6691
0.2006	61.0	1037	0.0573	25.0262	18.6691
0.2006	62.0	1054	0.0548	25.0514	18.6691
0.2006	63.0	1071	0.0545	25.036	18.6691
0.2006	64.0	1088	0.0526	25.2406	18.6691
0.2006	65.0	1105	0.0511	25.276	18.6691
0.2006	66.0	1122	0.0511	25.2682	18.6691
0.2006	67.0	1139	0.0504	25.1104	18.6691
0.2006	68.0	1156	0.0513	25.2775	18.6691
0.2006	69.0	1173	0.0479	25.5063	18.6691
0.2006	70.0	1190	0.0470	25.4453	18.6691
0.2006	71.0	1207	0.0468	25.4056	18.6691
0.2006	72.0	1224	0.0451	25.4968	18.6691
0.2006	73.0	1241	0.0441	25.6183	18.6691
0.2006	74.0	1258	0.0432	25.6308	18.6691
0.2006	75.0	1275	0.0428	25.4817	18.6691
0.2006	76.0	1292	0.0417	25.6171	18.6691
0.2006	77.0	1309	0.0414	25.4539	18.6691
0.2006	78.0	1326	0.0413	25.4539	18.6691
0.2006	79.0	1343	0.0399	25.3733	18.6691
0.2006	80.0	1360	0.0393	25.6878	18.6691
0.2006	81.0	1377	0.0391	25.6461	18.6691
0.2006	82.0	1394	0.0384	25.8403	18.6691
0.2006	83.0	1411	0.0381	25.9332	18.6691
0.2006	84.0	1428	0.0374	25.9369	18.6691
0.2006	85.0	1445	0.0371	25.8831	18.6691
0.2006	86.0	1462	0.0369	25.7971	18.6691
0.2006	87.0	1479	0.0364	25.8831	18.6691
0.2006	88.0	1496	0.0353	25.918	18.6691
0.1412	89.0	1513	0.0347	26.0189	18.6691
0.1412	90.0	1530	0.0342	25.9848	18.6691
0.1412	91.0	1547	0.0338	25.9848	18.6691
0.1412	92.0	1564	0.0326	25.9451	18.6691
0.1412	93.0	1581	0.0328	26.1168	18.6691
0.1412	94.0	1598	0.0321	26.1039	18.6691
0.1412	95.0	1615	0.0318	26.1391	18.6691
0.1412	96.0	1632	0.0329	26.1391	18.6691
0.1412	97.0	1649	0.0299	26.1745	18.6691
0.1412	98.0	1666	0.0303	26.1917	18.6691
0.1412	99.0	1683	0.0290	26.0001	18.6691
0.1412	100.0	1700	0.0311	26.0437	18.6691
0.1412	101.0	1717	0.0280	26.1231	18.6691
0.1412	102.0	1734	0.0288	26.2359	18.6691
0.1412	103.0	1751	0.0279	26.2359	18.6691
0.1412	104.0	1768	0.0285	26.2976	18.6691
0.1412	105.0	1785	0.0263	26.3152	18.6691
0.1412	106.0	1802	0.0259	26.3548	18.6691
0.1412	107.0	1819	0.0255	26.3548	18.6691
0.1412	108.0	1836	0.0253	26.3548	18.6691
0.1412	109.0	1853	0.0241	26.377	18.6691
0.1412	110.0	1870	0.0247	26.3548	18.6691
0.1412	111.0	1887	0.0234	26.3901	18.6691
0.1412	112.0	1904	0.0224	26.4917	18.6691
0.1412	113.0	1921	0.0220	26.4297	18.6691
0.1412	114.0	1938	0.0223	26.3548	18.6691
0.1412	115.0	1955	0.0215	26.3548	18.6691
0.1412	116.0	1972	0.0211	26.3548	18.6691
0.1412	117.0	1989	0.0210	26.3548	18.6691
0.1097	118.0	2006	0.0204	26.3944	18.6691
0.1097	119.0	2023	0.0204	26.3944	18.6691
0.1097	120.0	2040	0.0200	26.3944	18.6691
0.1097	121.0	2057	0.0201	26.3944	18.6691
0.1097	122.0	2074	0.0196	26.3944	18.6691
0.1097	123.0	2091	0.0197	26.434	18.6691
0.1097	124.0	2108	0.0189	26.434	18.6691
0.1097	125.0	2125	0.0191	26.434	18.6691
0.1097	126.0	2142	0.0185	26.434	18.6691
0.1097	127.0	2159	0.0185	26.496	18.6691
0.1097	128.0	2176	0.0188	26.496	18.6691
0.1097	129.0	2193	0.0181	26.5709	18.6691
0.1097	130.0	2210	0.0179	26.5709	18.6691
0.1097	131.0	2227	0.0182	26.9088	18.7206
0.1097	132.0	2244	0.0180	26.936	18.7206
0.1097	133.0	2261	0.0173	26.936	18.7206
0.1097	134.0	2278	0.0176	26.936	18.7206
0.1097	135.0	2295	0.0167	26.936	18.7206
0.1097	136.0	2312	0.0181	26.8068	18.7206
0.1097	137.0	2329	0.0175	26.8738	18.7206
0.1097	138.0	2346	0.0158	26.8738	18.7206
0.1097	139.0	2363	0.0167	26.8738	18.7206
0.1097	140.0	2380	0.0166	26.8738	18.7206
0.1097	141.0	2397	0.0162	26.8738	18.7206
0.1097	142.0	2414	0.0160	26.8738	18.7206
0.1097	143.0	2431	0.0156	26.8738	18.7206
0.1097	144.0	2448	0.0160	26.8738	18.7206
0.1097	145.0	2465	0.0152	26.9135	18.7206
0.1097	146.0	2482	0.0148	26.9135	18.7206
0.1097	147.0	2499	0.0155	26.9135	18.7206
0.0913	148.0	2516	0.0149	26.9135	18.7206
0.0913	149.0	2533	0.0156	26.9135	18.7206
0.0913	150.0	2550	0.0155	26.9135	18.7206
0.0913	151.0	2567	0.0149	26.9135	18.7206
0.0913	152.0	2584	0.0142	26.9135	18.7206
0.0913	153.0	2601	0.0136	26.8738	18.7206
0.0913	154.0	2618	0.0141	26.8738	18.7206
0.0913	155.0	2635	0.0139	26.9135	18.7206
0.0913	156.0	2652	0.0136	26.9135	18.7206
0.0913	157.0	2669	0.0135	26.9135	18.7206
0.0913	158.0	2686	0.0141	26.9135	18.7206
0.0913	159.0	2703	0.0143	26.9135	18.7206
0.0913	160.0	2720	0.0134	26.9135	18.7206
0.0913	161.0	2737	0.0129	26.9135	18.7206
0.0913	162.0	2754	0.0129	26.9135	18.7206
0.0913	163.0	2771	0.0136	26.9135	18.7206
0.0913	164.0	2788	0.0131	26.9135	18.7206
0.0913	165.0	2805	0.0136	26.9135	18.7206
0.0913	166.0	2822	0.0131	26.9135	18.7206
0.0913	167.0	2839	0.0127	26.9135	18.7206
0.0913	168.0	2856	0.0128	26.9135	18.7206
0.0913	169.0	2873	0.0128	26.9533	18.7206
0.0913	170.0	2890	0.0131	26.9533	18.7206
0.0913	171.0	2907	0.0135	26.9533	18.7206
0.0913	172.0	2924	0.0132	26.9533	18.7206
0.0913	173.0	2941	0.0128	26.9533	18.7206
0.0913	174.0	2958	0.0127	26.9533	18.7206
0.0913	175.0	2975	0.0128	26.9533	18.7206
0.0913	176.0	2992	0.0127	26.9533	18.7206
0.0819	177.0	3009	0.0122	26.9533	18.7206
0.0819	178.0	3026	0.0119	26.9533	18.7206
0.0819	179.0	3043	0.0120	26.9533	18.7206
0.0819	180.0	3060	0.0123	26.9533	18.7206
0.0819	181.0	3077	0.0123	26.9533	18.7206
0.0819	182.0	3094	0.0122	26.9533	18.7206
0.0819	183.0	3111	0.0122	26.9533	18.7206
0.0819	184.0	3128	0.0121	26.9533	18.7206
0.0819	185.0	3145	0.0120	26.9533	18.7206
0.0819	186.0	3162	0.0119	26.9533	18.7206
0.0819	187.0	3179	0.0119	26.9533	18.7206
0.0819	188.0	3196	0.0120	26.9533	18.7206
0.0819	189.0	3213	0.0119	26.9533	18.7206
0.0819	190.0	3230	0.0117	26.9533	18.7206
0.0819	191.0	3247	0.0117	26.9533	18.7206
0.0819	192.0	3264	0.0117	26.9533	18.7206
0.0819	193.0	3281	0.0117	26.9533	18.7206
0.0819	194.0	3298	0.0117	26.9533	18.7206
0.0819	195.0	3315	0.0118	26.9533	18.7206
0.0819	196.0	3332	0.0118	26.9533	18.7206
0.0819	197.0	3349	0.0118	26.9533	18.7206
0.0819	198.0	3366	0.0117	26.9533	18.7206
0.0819	199.0	3383	0.0117	26.9533	18.7206
0.0819	200.0	3400	0.0117	26.9533	18.7206

Framework versions

• Transformers 4.21.1
• Pytorch 1.12.1+cu113
• Datasets 2.4.0
• Tokenizers 0.12.1