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t5-small-finetuned-xsum-wei1 – AI Model by bochaowei | AlphaNeural AI
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t5-small-finetuned-xsum-wei1
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transformers
pytorch
tensorboard
t5
text2text-generation
text-generation-inference
endpoints_compatible
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20% of the training data
license: apache-2.0 tags:
generated_from_trainer datasets:
xsum metrics:
rouge model-index:
name: t5-small-finetuned-xsum-wei1 results:
task: name: Sequence-to-sequence Language Modeling type: text2text-generation dataset: name: xsum type: xsum args: default metrics:
name: Rouge1 type: rouge value: 27.5875
t5-small-finetuned-xsum-wei1
This model is a fine-tuned version of
t5-small
on the xsum dataset. It achieves the following results on the evaluation set:
Loss: 2.5287
Rouge1: 27.5875
Rouge2: 7.4083
Rougel: 21.5654
Rougelsum: 21.5716
Gen Len: 18.8205
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: 12
eval_batch_size: 12
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
2.7677
1.0
3401
2.5441
27.4235
7.2208
21.3535
21.3636
18.8311
2.735
2.0
6802
2.5287
27.5875
7.4083
21.5654
21.5716
18.8205
Framework versions
Transformers 4.11.3
Pytorch 1.9.0+cu111
Datasets 1.14.0
Tokenizers 0.10.3
