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t5-small-xsum – AI Model by uzainfarooq | AlphaNeural AI
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uzainfarooq
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t5-small-xsum
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transformers
safetensors
t5
feature-extraction
generated_from_trainer
xsum
google-t5/t5-small
finetune
apache-2.0
text-generation-inference
endpoints_compatible
us
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t5-small-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: 0.6763
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: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
0.8842
1.0
250
0.7547
0.7909
2.0
500
0.6917
0.8064
3.0
750
0.6763
Framework versions
Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.1
Tokenizers 0.19.1
