t5-base-finetuned-qg-context-dataset – AI Model by Deigant | AlphaNeural AI

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Deigant/
t5-base-finetuned-qg-context-dataset

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text2text-generation

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t5-base-finetuned-qg-context-dataset

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

Loss: 1.6222
Rouge1: 36.2283
Rouge2: 16.0636
Rougel: 32.6282
Rougelsum: 32.6551

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: 4
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
No log	1.0	73	1.8864	32.9447	13.9495	27.5473	27.4092
No log	2.0	146	1.6866	35.1131	13.7925	30.7017	30.5957
No log	3.0	219	1.6392	30.4209	11.2611	27.0456	27.0847
No log	4.0	292	1.6222	36.2283	16.0636	32.6282	32.6551

Framework versions

Transformers 4.24.0
Pytorch 1.12.1+cu113
Datasets 2.6.1
Tokenizers 0.13.2