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arthurmluz/
ptt5-wikilingua-cstnews-1024

Name: ptt5-wikilingua-cstnews-1024
Availability: InStock

transformers

pytorch

text2text-generation

generated_from_trainer

arthurmluz/ptt5-wikilingua-30epochs

finetune

mit

text-generation-inference

endpoints_compatible

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ptt5-wikilingua-cstnews-1024

This model is a fine-tuned version of arthurmluz/ptt5-wikilingua-30epochs on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.1062
Rouge1: 0.2634
Rouge2: 0.2049
Rougel: 0.2461
Rougelsum: 0.2619
Gen Len: 18.871

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
No log	1.0	47	1.3346	0.1918	0.1194	0.161	0.1857	18.6452
No log	2.0	94	1.2279	0.2326	0.1626	0.1996	0.2285	18.871
No log	3.0	141	1.1763	0.2424	0.1692	0.2117	0.2381	18.871
No log	4.0	188	1.1496	0.2467	0.1761	0.2129	0.2347	18.871
1.727	5.0	235	1.1292	0.2579	0.188	0.2317	0.2515	18.871
1.727	6.0	282	1.1190	0.2516	0.1834	0.2256	0.2435	18.871
1.727	7.0	329	1.1059	0.2476	0.1806	0.2227	0.2404	18.871
1.727	8.0	376	1.0990	0.2468	0.1797	0.2217	0.2391	18.871
1.3202	9.0	423	1.0910	0.2587	0.1902	0.2339	0.2541	18.871
1.3202	10.0	470	1.0882	0.259	0.1908	0.2343	0.2545	18.871
1.3202	11.0	517	1.0885	0.2539	0.1886	0.2324	0.2505	18.871
1.3202	12.0	564	1.0883	0.2601	0.1957	0.2399	0.2582	18.871
1.1493	13.0	611	1.0881	0.2607	0.1962	0.2403	0.2583	18.871
1.1493	14.0	658	1.0866	0.2624	0.1976	0.2433	0.26	18.871
1.1493	15.0	705	1.0875	0.2641	0.2072	0.2477	0.2626	18.871
1.1493	16.0	752	1.0897	0.2641	0.2069	0.2477	0.2626	18.871
1.1493	17.0	799	1.0913	0.2641	0.2072	0.2477	0.2626	18.871
1.0308	18.0	846	1.0927	0.2634	0.2063	0.2474	0.2618	18.871
1.0308	19.0	893	1.0977	0.2634	0.2059	0.2473	0.2618	18.871
1.0308	20.0	940	1.0976	0.2634	0.2059	0.2473	0.2618	18.871
1.0308	21.0	987	1.0993	0.2632	0.2059	0.247	0.2616	18.871
0.9401	22.0	1034	1.1000	0.2634	0.2049	0.2461	0.2619	18.871
0.9401	23.0	1081	1.0997	0.2634	0.2049	0.2461	0.2619	18.871
0.9401	24.0	1128	1.1018	0.2634	0.2049	0.2461	0.2619	18.871
0.9401	25.0	1175	1.1045	0.2634	0.2049	0.2461	0.2619	18.871
0.8857	26.0	1222	1.1057	0.2634	0.2049	0.2461	0.2619	18.871
0.8857	27.0	1269	1.1061	0.2634	0.2049	0.2461	0.2619	18.871
0.8857	28.0	1316	1.1062	0.2634	0.2049	0.2461	0.2619	18.871
0.8857	29.0	1363	1.1061	0.2634	0.2049	0.2461	0.2619	18.871
0.8716	30.0	1410	1.1062	0.2634	0.2049	0.2461	0.2619	18.871

Framework versions

Transformers 4.34.0
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.14.1

arthurmluz/ptt5-wikilingua-cstnews-1024

ptt5-wikilingua-cstnews-1024

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

arthurmluz/
ptt5-wikilingua-cstnews-1024