t5-base-finetuned-scitldr – AI Model by witchling22 | AlphaNeural AI

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witchling22/
t5-base-finetuned-scitldr

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text2text-generation

generated_from_trainer

google-t5/t5-base

text-generation-inference

endpoints_compatible

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t5-base-finetuned-scitldr

This model is a fine-tuned version of t5-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 3.1055
Rouge1: 23.6222
Rouge2: 10.2432
Rougel: 19.702
Rougelsum: 20.9458
Gen Len: 18.979

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: 4e-05
train_batch_size: 2
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
2.4272	0.1	100	3.1951	23.0447	9.7818	19.0676	20.1677	18.9532
2.0362	0.2	200	3.1715	23.5443	10.1156	19.5788	20.6995	18.9483
2.188	0.3	300	3.1067	24.2387	10.3059	20.0964	21.2592	18.9338
2.0312	0.4	400	3.1092	23.3168	10.1308	19.4275	20.611	18.9742
2.012	0.5	500	3.1189	23.6989	10.3005	19.7634	20.9462	18.9758
2.0581	0.6	600	3.1191	23.6818	10.2636	19.7953	20.9935	18.9774
2.0067	0.7	700	3.1297	23.8476	10.5139	19.9696	21.1594	18.9774
2.0049	0.8	800	3.1150	23.6929	10.3243	19.7895	21.0455	18.979
2.1839	0.9	900	3.1055	23.6222	10.2432	19.702	20.9458	18.979

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0