Beta
Explore
Marketplace
Neural Labs
Chat
Wallet
Docs
xlnet-large-cased-detect-dep – AI Model by Trong-Nghia | AlphaNeural AI
You can deploy this model and start earning money today!
Trong-Nghia
/
xlnet-large-cased-detect-dep
like
0
transformers
pytorch
tensorboard
xlnet
text-classification
generated_from_trainer
mit
autotrain_compatible
endpoints_compatible
us
Views
No views yet
Model card
Files and Versions
Community
API
Deploy
xlnet-large-cased-detect-dep
This model is a fine-tuned version of
xlnet-large-cased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.5463
Accuracy: 0.743
F1: 0.8152
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-06
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
0.6479
1.0
751
0.5937
0.7
0.7981
0.5988
2.0
1502
0.5463
0.743
0.8152
Framework versions
Transformers 4.30.1
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.13.3
