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t5-small-finetuned-xsum – AI Model by Ahmed-shetaia | 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: 2.4780
Rouge1: 28.3005
Rouge2: 7.7413
Rougel: 22.2784
Rougelsum: 22.2767
Gen Len: 18.8253
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: 16
eval_batch_size: 16
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
2.7074
1.0
12753
2.4780
28.3005
7.7413
22.2784
22.2767
18.8253
Framework versions
Transformers 4.45.1
Pytorch 2.4.0
Datasets 3.0.1
Tokenizers 0.20.0
