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t5-small-finetuned-xsum – AI Model by jgoodie | AlphaNeural AI
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t5-small-finetuned-xsum
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transformers
pytorch
t5
text2text-generation
generated_from_trainer
xsum
apache-2.0
model-index
text-generation-inference
endpoints_compatible
us
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t5-small-finetuned-xsum
This model is a fine-tuned version of
t5-small
on the xsum dataset. It achieves the following results on the evaluation set:
Loss: 2.4768
Rouge1: 28.5758
Rouge2: 7.9219
Rougel: 22.5161
Rougelsum: 22.5215
Gen Len: 18.8288
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: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Rouge1
Rouge2
Rougel
Rougelsum
Gen Len
2.7504
1.0
6377
2.5012
28.218
7.6611
22.1733
22.1702
18.8299
2.7148
2.0
12754
2.4768
28.5758
7.9219
22.5161
22.5215
18.8288
Framework versions
Transformers 4.25.1
Pytorch 1.13.1+cu117
Datasets 2.8.0
Tokenizers 0.13.2
