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