t5-large-SQuAD-qag-ep6

Zekunli/t5-large-SQuAD-qag-ep6

t5-large-SQuAD-qag-ep6 is a machine learning model from Zekunli. 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: Jun 7, 2023
Updated: Jun 7, 2023
SHA: 047de9fe

Model card

From the Hugging Face model README

t5-large-SQuAD-qag-ep6

This model is a fine-tuned version of t5-large on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.8950
Rouge1: 41.0251
Rouge2: 19.2729
Rougel: 37.4514
Rougelsum: 37.4839
F1: 20.0159
Exact Match: 14.2719
Gen Len: 18.418

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: 24
eval_batch_size: 48
seed: 1799
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	F1	Exact Match	Gen Len
1.1752	0.51	400	0.9542	39.054	17.5678	35.471	35.4744	16.7879	10.8853	18.5186
1.0232	1.02	800	0.9232	40.062	18.493	36.4108	36.4335	18.7316	12.9173	18.4543
0.9641	1.52	1200	0.9112	40.6835	19.0484	37.0867	37.1329	19.3326	14.03	18.4078
0.9422	2.03	1600	0.9044	40.9087	19.2513	37.3069	37.3196	19.999	14.2719	18.4383
0.8989	2.54	2000	0.9026	41.0666	19.4921	37.4916	37.5115	21.0451	14.8041	18.3469
0.9015	3.05	2400	0.8986	40.471	18.8468	36.9384	36.9357	19.3467	13.8365	18.4557
0.8679	3.56	2800	0.8950	41.0251	19.2729	37.4514	37.4839	20.0159	14.2719	18.418
0.8521	4.07	3200	0.8982	41.1633	19.6433	37.6253	37.6541	21.0075	15.046	18.3807
0.8362	4.57	3600	0.8972	40.9127	19.4618	37.4	37.4431	20.9531	14.8524	18.3503
0.8415	5.08	4000	0.8970	41.2265	19.7241	37.7405	37.7653	21.5704	15.1911	18.388
0.8312	5.59	4400	0.8966	40.9824	19.4891	37.533	37.5485	20.8781	14.7073	18.3967

Framework versions

Transformers 4.18.0
Pytorch 1.11.0+cu113
Datasets 2.5.1
Tokenizers 0.12.1

Library: transformers
Type: t5
License: apache-2.0
Created: Jun 7, 2023
Updated: Jun 7, 2023