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T5-Small-XSUM-Summarizer – AI Model by AirrStorm | AlphaNeural AI
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AirrStorm
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T5-Small-XSUM-Summarizer
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transformers
safetensors
t5
text2text-generation
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-Summarizer
This model is a fine-tuned version of
t5-small
on the xsum dataset. It achieves the following results on the evaluation set:
Loss: 0.4952
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: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
0.558
1.0
6250
0.5062
0.5416
2.0
12500
0.4974
0.5274
3.0
18750
0.4952
Framework versions
Transformers 4.48.0
Pytorch 2.5.1+cu124
Datasets 3.2.0
Tokenizers 0.21.0
