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t5-small-billsum – AI Model by StatsGary | AlphaNeural AI
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t5-small-billsum
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transformers
pytorch
t5
text2text-generation
generated_from_trainer
billsum
apache-2.0
model-index
text-generation-inference
endpoints_compatible
us
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t5-small-billsum
This model is a fine-tuned version of
t5-small
on the billsum dataset. It achieves the following results on the evaluation set:
Loss: 2.5953
Rouge1: 0.1383
Rouge2: 0.0487
Rougel: 0.1135
Rougelsum: 0.1132
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: 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: 2
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Rouge1
Rouge2
Rougel
Rougelsum
Gen Len
No log
1.0
124
2.6810
0.1312
0.0415
0.1076
0.1077
19.0
No log
2.0
248
2.5953
0.1383
0.0487
0.1135
0.1132
19.0
Framework versions
Transformers 4.25.1
Pytorch 1.13.1+cu116
Datasets 2.8.0
Tokenizers 0.13.2
