finalgenz

This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.2203
• Bleu: 40.3273
• Gen Len: 15.1799

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: 2e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Bleu	Gen Len
No log	1.0	107	1.9829	29.4484	15.4626
No log	2.0	214	1.7854	34.3033	15.3762
No log	3.0	321	1.6918	34.328	15.6005
No log	4.0	428	1.6259	34.9122	15.6355
1.9708	5.0	535	1.5824	35.7506	15.5234
1.9708	6.0	642	1.5423	36.1821	15.5631
1.9708	7.0	749	1.5127	36.4014	15.5935
1.9708	8.0	856	1.4867	36.6811	15.5023
1.9708	9.0	963	1.4611	36.7295	15.493
1.5688	10.0	1070	1.4387	36.7706	15.4533
1.5688	11.0	1177	1.4229	37.2131	15.3808
1.5688	12.0	1284	1.4026	36.7912	15.3879
1.5688	13.0	1391	1.3865	37.3493	15.3435
1.5688	14.0	1498	1.3732	37.5175	15.3528
1.4261	15.0	1605	1.3587	37.2673	15.2827
1.4261	16.0	1712	1.3476	37.432	15.3668
1.4261	17.0	1819	1.3386	37.7461	15.3318
1.4261	18.0	1926	1.3277	37.2703	15.3598
1.3271	19.0	2033	1.3173	37.2506	15.4463
1.3271	20.0	2140	1.3120	38.1016	15.3294
1.3271	21.0	2247	1.3060	38.2439	15.285
1.3271	22.0	2354	1.2969	38.2214	15.3341
1.3271	23.0	2461	1.2901	38.3322	15.2921
1.2495	24.0	2568	1.2821	38.4395	15.3037
1.2495	25.0	2675	1.2780	38.483	15.2523
1.2495	26.0	2782	1.2722	38.5899	15.278
1.2495	27.0	2889	1.2682	38.7772	15.2103
1.2495	28.0	2996	1.2635	38.964	15.2126
1.1999	29.0	3103	1.2576	39.236	15.215
1.1999	30.0	3210	1.2532	38.9925	15.1752
1.1999	31.0	3317	1.2509	38.8058	15.1986
1.1999	32.0	3424	1.2474	39.1842	15.2173
1.1609	33.0	3531	1.2425	39.6325	15.2547
1.1609	34.0	3638	1.2405	39.5175	15.2407
1.1609	35.0	3745	1.2371	39.4547	15.222
1.1609	36.0	3852	1.2363	39.3411	15.1986
1.1609	37.0	3959	1.2341	39.5572	15.2266
1.1278	38.0	4066	1.2306	39.7315	15.243
1.1278	39.0	4173	1.2299	39.9935	15.2383
1.1278	40.0	4280	1.2283	39.8349	15.2033
1.1278	41.0	4387	1.2257	40.0669	15.2196
1.1278	42.0	4494	1.2247	39.8818	15.2079
1.107	43.0	4601	1.2241	40.2504	15.1846
1.107	44.0	4708	1.2225	40.2175	15.2126
1.107	45.0	4815	1.2219	40.1115	15.2009
1.107	46.0	4922	1.2212	40.1396	15.1916
1.0941	47.0	5029	1.2208	40.1478	15.1963
1.0941	48.0	5136	1.2205	40.171	15.1846
1.0941	49.0	5243	1.2203	40.2113	15.1659
1.0941	50.0	5350	1.2203	40.3273	15.1799

Framework versions

• Transformers 4.31.0
• Pytorch 2.0.1+cu118
• Datasets 2.14.3
• Tokenizers 0.13.3