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t5-small-finetuned-xsum – AI Model by mdaffarudiyanto | AlphaNeural AI
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t5-small-finetuned-xsum
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transformers
tensorboard
safetensors
t5
text2text-generation
generated_from_trainer
xsum
google-t5/t5-small
finetune
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: 2.4196
Rouge1: 29.5094
Rouge2: 8.6236
Rougel: 23.3694
Rougelsum: 23.3554
Gen Len: 18.8456
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: 0.0001
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: 1
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Rouge1
Rouge2
Rougel
Rougelsum
Gen Len
2.6817
1.0
25506
2.4196
29.5094
8.6236
23.3694
23.3554
18.8456
Framework versions
Transformers 4.39.3
Pytorch 2.2.2+cu121
Datasets 2.18.0
Tokenizers 0.15.2
