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xlnet-base-cased-finetuned-PRC – AI Model by agarc15 | AlphaNeural AI
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agarc15
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xlnet-base-cased-finetuned-PRC
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transformers
pytorch
tensorboard
xlnet
text-classification
generated_from_trainer
xlnet/xlnet-base-cased
finetune
mit
autotrain_compatible
endpoints_compatible
us
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xlnet-base-cased-finetuned-PRC
This model is a fine-tuned version of
xlnet-base-cased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.5563
Accuracy: 0.8722
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: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
1.0
391
0.5250
0.8543
0.6755
2.0
782
0.4992
0.8651
0.378
3.0
1173
0.5368
0.8622
0.2558
4.0
1564
0.5563
0.8722
0.2558
5.0
1955
0.5695
0.8719
Framework versions
Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3
