extract_long_text_unbalanced_smaller_6

Sheng-Yen/extract_long_text_unbalanced_smaller_6

extract_long_text_unbalanced_smaller_6 is a machine learning model from Sheng-Yen. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.

should probably proofread and complete it, then remove this comment. --

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At a glance

Library: transformers
Model type: t5
Access: Public
Created: Mar 31, 2024
Updated: Mar 31, 2024
SHA: fd580cf1

Base models

weny22/sum_model_t5_saved

Model card

From the Hugging Face model README

extract_long_text_unbalanced_smaller_6

This model is a fine-tuned version of weny22/sum_model_t5_saved on the None dataset. It achieves the following results on the evaluation set:

Loss: 2.2687
Rouge1: 0.2023
Rouge2: 0.0727
Rougel: 0.1638
Rougelsum: 0.1637
Gen Len: 18.9793

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: 0.002
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	335	2.3733	0.1898	0.059	0.1502	0.1501	18.9833
3.2662	2.0	670	2.2397	0.185	0.0609	0.1493	0.1492	18.962
2.392	3.0	1005	2.1809	0.191	0.0655	0.1545	0.1544	18.9607
2.392	4.0	1340	2.1512	0.1923	0.0675	0.1552	0.1551	18.972
2.1606	5.0	1675	2.1182	0.1938	0.0689	0.1571	0.1571	18.974
2.0276	6.0	2010	2.1242	0.1944	0.0671	0.1576	0.1575	18.9733
2.0276	7.0	2345	2.1003	0.1944	0.0683	0.1578	0.1578	18.9833
1.8856	8.0	2680	2.1301	0.1993	0.0718	0.1619	0.162	18.9907
1.7948	9.0	3015	2.1103	0.1978	0.0692	0.1605	0.1605	18.978
1.7948	10.0	3350	2.1220	0.1999	0.0716	0.1628	0.1627	18.9773
1.683	11.0	3685	2.1290	0.1981	0.0699	0.1604	0.1606	18.982
1.6151	12.0	4020	2.1430	0.2024	0.0727	0.1632	0.1632	18.9793
1.6151	13.0	4355	2.1486	0.1976	0.0721	0.1606	0.1607	18.9813
1.5263	14.0	4690	2.1857	0.2032	0.0737	0.1645	0.1645	18.9873
1.4647	15.0	5025	2.2031	0.2029	0.0719	0.1639	0.164	18.9873
1.4647	16.0	5360	2.2044	0.2043	0.0744	0.1659	0.1659	18.9853
1.3972	17.0	5695	2.2325	0.2031	0.0724	0.1637	0.1638	18.9867
1.3577	18.0	6030	2.2473	0.2031	0.0724	0.164	0.1639	18.98
1.3577	19.0	6365	2.2544	0.2029	0.0733	0.1638	0.164	18.984
1.3132	20.0	6700	2.2687	0.2023	0.0727	0.1638	0.1637	18.9793

Framework versions

Transformers 4.39.1
Pytorch 2.2.2+cu121
Datasets 2.18.0
Tokenizers 0.15.2

Library: transformers
Type: t5
Created: Mar 31, 2024
Updated: Mar 31, 2024