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summarize_t5-small_billsum_finetune – AI Model by jonastokoliu | AlphaNeural AI
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summarize_t5-small_billsum_finetune
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transformers
pytorch
tensorboard
t5
text2text-generation
generated_from_trainer
billsum
apache-2.0
model-index
text-generation-inference
endpoints_compatible
us
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summarize_t5-small_billsum_finetune
This model is a fine-tuned version of
t5-small
on the billsum dataset. It achieves the following results on the evaluation set:
Loss: 3.0625
Rouge1: 0.1317
Rouge2: 0.0435
Rougel: 0.1125
Rougelsum: 0.1127
Gen Len: 20.0
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: 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
No log
1.0
31
3.2722
0.1362
0.0466
0.1158
0.116
20.0
No log
2.0
62
3.0625
0.1317
0.0435
0.1125
0.1127
20.0
Framework versions
Transformers 4.29.2
Pytorch 2.0.1+cu117
Datasets 2.12.0
Tokenizers 0.13.3
