flan-t5-2048-input-30-epochs

tanatapanun/flan-t5-2048-input-30-epochs

flan-t5-2048-input-30-epochs is a machine learning model from tanatapanun. 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. 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

Library: transformers
License: apache-2.0
Model type: t5
Access: Public
Created: Dec 13, 2023
Updated: Dec 14, 2023
SHA: e5dfc9df

Base models

tanatapanun/flan-t5-2048-input-1-epochs

Model card

From the Hugging Face model README

flan-t5-2048-input-30-epochs

This model is a fine-tuned version of tanatapanun/flan-t5-2048-input-1-epochs on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.7695
Rouge1: 0.2731
Rouge2: 0.1008
Rougel: 0.2328
Rougelsum: 0.2319
Gen Len: 13.82

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: 4
eval_batch_size: 4
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	301	1.5244	0.2018	0.0697	0.1768	0.1758	11.98
2.3092	2.0	602	0.8884	0.2155	0.0817	0.1857	0.1837	14.36
2.3092	3.0	903	0.8211	0.2112	0.0739	0.1784	0.1772	15.2
0.9906	4.0	1204	0.8055	0.2205	0.082	0.1854	0.1844	14.71
0.8522	5.0	1505	0.7995	0.2381	0.084	0.2025	0.2026	14.59
0.8522	6.0	1806	0.7937	0.2449	0.0775	0.2046	0.2032	15.15
0.8235	7.0	2107	0.7917	0.2535	0.0882	0.2116	0.2104	14.57
0.8235	8.0	2408	0.7856	0.263	0.0848	0.2198	0.2195	14.36
0.7869	9.0	2709	0.7832	0.2759	0.097	0.2371	0.2347	13.82
0.7702	10.0	3010	0.7810	0.2622	0.0884	0.225	0.2253	14.16
0.7702	11.0	3311	0.7791	0.2807	0.0995	0.2384	0.2376	14.11
0.7721	12.0	3612	0.7786	0.2758	0.0896	0.237	0.2362	14.17
0.7721	13.0	3913	0.7772	0.2851	0.094	0.2466	0.2456	14.05
0.7534	14.0	4214	0.7747	0.2642	0.0929	0.2245	0.2235	13.95
0.7285	15.0	4515	0.7739	0.2681	0.0993	0.2281	0.2289	13.81
0.7285	16.0	4816	0.7746	0.2714	0.0978	0.2309	0.2302	14.02
0.7334	17.0	5117	0.7727	0.2734	0.0957	0.2317	0.2311	14.0
0.7334	18.0	5418	0.7720	0.2729	0.0996	0.2321	0.2321	13.92
0.7193	19.0	5719	0.7726	0.2693	0.0982	0.2298	0.2291	13.88
0.7147	20.0	6020	0.7727	0.2799	0.103	0.2378	0.2368	13.91
0.7147	21.0	6321	0.7715	0.2856	0.1047	0.2465	0.2451	13.83
0.7204	22.0	6622	0.7704	0.2724	0.1016	0.2339	0.233	13.91
0.7204	23.0	6923	0.7705	0.2751	0.1017	0.2344	0.2335	13.96
0.6853	24.0	7224	0.7697	0.2746	0.1011	0.2343	0.2333	13.73
0.7116	25.0	7525	0.7703	0.2757	0.1024	0.2357	0.2348	13.72
0.7116	26.0	7826	0.7698	0.2745	0.1008	0.2341	0.2333	13.72
0.6935	27.0	8127	0.7699	0.2731	0.1008	0.2328	0.2319	13.82
0.6935	28.0	8428	0.7698	0.2731	0.1008	0.2328	0.2319	13.82
0.7051	29.0	8729	0.7695	0.2731	0.1008	0.2328	0.2319	13.82
0.6923	30.0	9030	0.7695	0.2731	0.1008	0.2328	0.2319	13.82

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0

Library: transformers
Type: t5
License: apache-2.0
Created: Dec 13, 2023
Updated: Dec 14, 2023