flan-t5-large-extraction-cnndm_4000-all-new – AI Model by Zekunli | AlphaNeural AI

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flan-t5-large-extraction-cnndm_4000-all-new

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flan-t5-large-extraction-cnndm_4000-all-new

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

Loss: 1.7217
Rouge1: 35.7039
Rouge2: 15.7172
Rougel: 30.4548
Rougelsum: 30.4927
Gen Len: 19.0

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: 16
eval_batch_size: 48
seed: 1799
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
2.1171	0.8	200	1.7879	33.136	13.8435	28.2659	28.2963	19.0
1.8929	1.6	400	1.7502	34.0512	14.7178	29.4891	29.4818	18.99
1.8254	2.4	600	1.7331	35.166	15.5654	30.1143	30.1629	18.99
1.7543	3.2	800	1.7371	35.4455	15.7511	30.7242	30.6975	19.0
1.7053	4.0	1000	1.7217	35.7039	15.7172	30.4548	30.4927	19.0
1.6508	4.8	1200	1.7275	35.0989	15.6698	30.0472	30.0981	19.0
1.6029	5.6	1400	1.7308	35.3936	16.1155	30.5695	30.633	19.0
1.5741	6.4	1600	1.7547	35.4065	15.9775	30.4598	30.5162	19.0
1.5497	7.2	1800	1.7508	35.5377	16.0075	30.5775	30.5533	19.0
1.5029	8.0	2000	1.7498	34.9215	15.4151	29.8118	29.802	19.0

Framework versions

Transformers 4.18.0
Pytorch 1.10.0+cu111
Datasets 2.5.1
Tokenizers 0.12.1