long_text_balanced_smaller_original_text

weny22/long_text_balanced_smaller_original_text

long_text_balanced_smaller_original_text is a machine learning model from weny22. 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 26, 2024
Updated: Mar 27, 2024
SHA: ea9a1212

Base models

weny22/sum_model_t5_saved

Model card

From the Hugging Face model README

long_text_balanced_smaller_original_text

The model trained with balanced dataset, without preprocess the training data.

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: 2.3143
Rouge1: 0.2101
Rouge2: 0.0804
Rougel: 0.1705
Rougelsum: 0.1707
Gen Len: 18.986

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	119	2.3387	0.1849	0.0583	0.1474	0.1475	18.98
No log	2.0	238	2.1768	0.1954	0.0647	0.1538	0.1537	18.9707
No log	3.0	357	2.1282	0.1952	0.0637	0.1537	0.1536	18.9947
No log	4.0	476	2.1173	0.1953	0.0683	0.1559	0.1557	18.9813
2.7944	5.0	595	2.0873	0.2022	0.0743	0.1624	0.1623	18.976
2.7944	6.0	714	2.0851	0.2054	0.0769	0.1652	0.1653	18.9887
2.7944	7.0	833	2.0948	0.2043	0.0762	0.1633	0.1632	18.972
2.7944	8.0	952	2.1123	0.1992	0.0745	0.1607	0.1605	18.9673
1.9807	9.0	1071	2.1280	0.2067	0.0779	0.1669	0.1669	18.9767
1.9807	10.0	1190	2.1251	0.2124	0.0801	0.1705	0.1704	18.99
1.9807	11.0	1309	2.1286	0.2069	0.0772	0.1668	0.1668	18.9927
1.9807	12.0	1428	2.1592	0.2096	0.0786	0.1688	0.1689	18.972
1.6485	13.0	1547	2.1811	0.2069	0.0789	0.1688	0.1689	18.9973
1.6485	14.0	1666	2.2124	0.2089	0.079	0.1686	0.1688	18.968
1.6485	15.0	1785	2.2187	0.2107	0.0797	0.1693	0.1695	18.9893
1.6485	16.0	1904	2.2438	0.2097	0.0793	0.1695	0.1695	18.9787
1.4186	17.0	2023	2.2685	0.2092	0.0799	0.1692	0.1693	18.99
1.4186	18.0	2142	2.2733	0.2085	0.0788	0.1684	0.1686	18.9747
1.4186	19.0	2261	2.2947	0.2087	0.0803	0.1696	0.1696	18.9813
1.4186	20.0	2380	2.3143	0.2101	0.0804	0.1705	0.1707	18.986

Framework versions

Transformers 4.38.2
Pytorch 2.1.2+cu121
Datasets 2.18.0
Tokenizers 0.15.2

Library: transformers
Type: t5
Created: Mar 26, 2024
Updated: Mar 27, 2024