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arthurmluz/
ptt5-wikilingua-30epochs

Name: ptt5-wikilingua-30epochs
Availability: InStock

transformers

pytorch

text2text-generation

generated_from_trainer

unicamp-dl/ptt5-base-portuguese-vocab

finetune

mit

text-generation-inference

endpoints_compatible

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ptt5-wikilingua-30epochs

This model is a fine-tuned version of unicamp-dl/ptt5-base-portuguese-vocab on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.9063
Rouge1: 0.2604
Rouge2: 0.1127
Rougel: 0.2222
Rougelsum: 0.2541
Gen Len: 18.4528

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: 2
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
2.1668	1.0	28580	2.0384	0.2366	0.0935	0.2034	0.2311	18.2195
2.0348	2.0	57160	1.9725	0.2448	0.0998	0.2098	0.2391	18.3898
2.0152	3.0	85740	1.9346	0.2469	0.1024	0.2122	0.2414	18.2427
1.9769	4.0	114320	1.9096	0.2503	0.1047	0.2147	0.2446	18.2773
1.8471	5.0	142900	1.8957	0.253	0.1076	0.2169	0.2473	18.2612
1.8504	6.0	171480	1.8840	0.2541	0.1084	0.2179	0.2483	18.3317
1.7456	7.0	200060	1.8768	0.2547	0.1084	0.2183	0.2488	18.3634
1.7254	8.0	228640	1.8747	0.2563	0.1099	0.2196	0.2505	18.3577
1.7742	9.0	257220	1.8739	0.2562	0.11	0.2194	0.2504	18.3904
1.7211	10.0	285800	1.8667	0.2572	0.1109	0.2205	0.2513	18.3616
1.696	11.0	314380	1.8677	0.2568	0.1112	0.2204	0.251	18.349
1.6762	12.0	342960	1.8695	0.2571	0.1108	0.2202	0.2513	18.3528
1.6404	13.0	371540	1.8738	0.2582	0.1115	0.2208	0.2523	18.3909
1.6523	14.0	400120	1.8727	0.259	0.1118	0.2215	0.253	18.4077
1.626	15.0	428700	1.8736	0.2596	0.1124	0.2222	0.2537	18.4245
1.5922	16.0	457280	1.8750	0.259	0.1123	0.2215	0.253	18.4125
1.5345	17.0	485860	1.8783	0.2591	0.112	0.2214	0.2529	18.4013
1.5785	18.0	514440	1.8797	0.2588	0.112	0.2212	0.2527	18.3965
1.5097	19.0	543020	1.8868	0.2592	0.1115	0.221	0.2531	18.4567
1.5091	20.0	571600	1.8851	0.2593	0.1124	0.2216	0.2533	18.397
1.5116	21.0	600180	1.8895	0.2599	0.1124	0.2219	0.2537	18.4505
1.5351	22.0	628760	1.8901	0.2606	0.113	0.2225	0.2544	18.4369
1.5125	23.0	657340	1.8953	0.2598	0.1125	0.2218	0.2535	18.4273
1.5246	24.0	685920	1.8980	0.2609	0.1129	0.2226	0.2544	18.4464
1.5113	25.0	714500	1.8990	0.2604	0.1127	0.2221	0.2542	18.4562
1.4814	26.0	743080	1.9029	0.261	0.1133	0.223	0.2547	18.4634
1.5212	27.0	771660	1.9014	0.2606	0.1129	0.2226	0.2544	18.4458
1.4469	28.0	800240	1.9032	0.2609	0.1129	0.2226	0.2546	18.4577
1.4844	29.0	828820	1.9050	0.2602	0.1125	0.2221	0.2539	18.4553
1.4561	30.0	857400	1.9063	0.2604	0.1127	0.2222	0.2541	18.4528

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3

arthurmluz/ptt5-wikilingua-30epochs

ptt5-wikilingua-30epochs

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

arthurmluz/
ptt5-wikilingua-30epochs