text_summarization-finetuned

RMWeerasinghe/text_summarization-finetuned

text_summarization-finetuned is a summarization model from RMWeerasinghe. Use it when you need a shorter version of a longer text. It is set up for transformers. The card lists the license as apache-2.0.

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

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At a glance

Task: Summarization
Library: transformers
License: apache-2.0
Model type: t5
Access: Public
Created: Feb 11, 2024
Updated: Feb 12, 2024
SHA: 196921a4

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Base models

Falconsai/text_summarization

Datasets

cnn_dailymail

Model card

From the Hugging Face model README

text_summarization-finetuned

This model is a fine-tuned version of Falconsai/text_summarization on the cnn_dailymail dataset. It achieves the following results on the evaluation set:

Loss: 1.8119
Rouge1: 0.2389
Rouge2: 0.1112
Rougel: 0.1946
Rougelsum: 0.2237

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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 40

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
10.7536	1.0	78	6.6776	0.203	0.0868	0.1627	0.1909
5.0057	1.99	156	3.2391	0.2128	0.0909	0.1707	0.2003
3.3921	2.99	234	2.9233	0.2263	0.102	0.1849	0.213
3.1013	4.0	313	2.7724	0.2265	0.1043	0.1864	0.2128
2.9643	5.0	391	2.5935	0.2305	0.1075	0.1893	0.2166
2.7594	5.99	469	2.4411	0.2311	0.1075	0.1888	0.2171
2.6579	6.99	547	2.3273	0.2327	0.1084	0.1908	0.2185
2.5729	8.0	626	2.2452	0.2326	0.1083	0.1905	0.2185
2.4879	9.0	704	2.1828	0.2313	0.1063	0.1893	0.2176
2.401	9.99	782	2.1365	0.2336	0.1071	0.1907	0.2193
2.346	10.99	860	2.0937	0.2332	0.1065	0.1905	0.2192
2.3086	12.0	939	2.0606	0.2334	0.107	0.1905	0.2191
2.2648	13.0	1017	2.0315	0.2351	0.1085	0.1925	0.2211
2.2452	13.99	1095	2.0058	0.2354	0.1079	0.1922	0.221
2.204	14.99	1173	1.9853	0.2364	0.1093	0.1932	0.2222
2.1723	16.0	1252	1.9665	0.236	0.109	0.1931	0.2218
2.1601	17.0	1330	1.9479	0.2356	0.109	0.1923	0.2212
2.143	17.99	1408	1.9337	0.2356	0.1093	0.1926	0.2215
2.093	18.99	1486	1.9201	0.2366	0.1101	0.193	0.2223
2.0987	20.0	1565	1.9077	0.2371	0.111	0.1938	0.2228
2.0663	21.0	1643	1.8956	0.2368	0.1104	0.1937	0.2219
2.0629	21.99	1721	1.8858	0.2375	0.1109	0.1935	0.2221
2.0449	22.99	1799	1.8765	0.2395	0.1128	0.1959	0.2244
2.0342	24.0	1878	1.8684	0.2384	0.1115	0.1943	0.2233
2.0021	25.0	1956	1.8620	0.2373	0.1101	0.1932	0.222
2.0152	25.99	2034	1.8537	0.2387	0.1116	0.1949	0.2236
2.0058	26.99	2112	1.8477	0.239	0.1118	0.195	0.224
1.981	28.0	2191	1.8418	0.2377	0.1108	0.194	0.2227
1.9493	29.0	2269	1.8358	0.2388	0.111	0.1947	0.2234
1.9626	29.99	2347	1.8314	0.2385	0.1109	0.1945	0.223
1.9735	30.99	2425	1.8279	0.239	0.1109	0.1944	0.2232
1.9421	32.0	2504	1.8240	0.2393	0.1109	0.1946	0.2234
1.9371	33.0	2582	1.8212	0.2396	0.1114	0.1951	0.2239
1.9252	33.99	2660	1.8184	0.2392	0.1111	0.1947	0.2238
1.9556	34.99	2738	1.8163	0.2392	0.1111	0.1946	0.2238
1.9436	36.0	2817	1.8147	0.2394	0.111	0.1945	0.224
1.9444	37.0	2895	1.8132	0.239	0.1113	0.1946	0.2239
1.9368	37.99	2973	1.8125	0.239	0.1112	0.1947	0.2239
1.9467	38.99	3051	1.8120	0.2389	0.1112	0.1946	0.2237
1.9335	39.87	3120	1.8119	0.2389	0.1112	0.1946	0.2237

Framework versions

Transformers 4.38.0.dev0
Pytorch 2.2.0
Datasets 2.16.1
Tokenizers 0.15.1

Task: Summarization
Library: transformers
Type: t5
License: apache-2.0
Created: Feb 11, 2024
Updated: Feb 12, 2024