t5-large-qa – AI Model by ra4wv2 | AlphaNeural AI

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ra4wv2/
t5-large-qa

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text2text-generation

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text-generation-inference

endpoints_compatible

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t5-large-qa

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

Loss: 0.1241
Rouge1: 77.7328
Rouge2: 66.0005
Rougel: 77.1753
Rougelsum: 77.1453
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: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	306	0.1274	77.6174	66.4422	77.0276	77.0702	19.0
0.1965	2.0	612	0.1241	77.7328	66.0005	77.1753	77.1453	19.0
0.1965	3.0	918	0.1310	77.8688	67.4016	77.5375	77.5445	19.0
0.083	4.0	1224	0.1385	78.1193	67.0951	77.5954	77.63	19.0
0.0474	5.0	1530	0.1464	78.1002	67.0309	77.5527	77.5764	19.0

Framework versions

Transformers 4.28.0
Pytorch 2.0.0+cu118
Datasets 2.12.0
Tokenizers 0.13.3