Regression_xlnet_NOaug_MSEloss

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: 0.6460
• Mse: 0.6460
• Mae: 0.7041
• R2: -0.1893
• Accuracy: 0.2632

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: 1e-12
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Mse	Mae	R2	Accuracy
No log	1.0	33	0.7342	0.7342	0.7706	-1.1938	0.2703
No log	2.0	66	0.7342	0.7342	0.7706	-1.1938	0.2703
No log	3.0	99	0.7342	0.7342	0.7706	-1.1938	0.2703
No log	4.0	132	0.7342	0.7342	0.7706	-1.1938	0.2703
No log	5.0	165	0.7342	0.7342	0.7706	-1.1938	0.2703
No log	6.0	198	0.7342	0.7342	0.7706	-1.1938	0.2703
No log	7.0	231	0.7342	0.7342	0.7706	-1.1938	0.2703
No log	8.0	264	0.7342	0.7342	0.7706	-1.1938	0.2703
No log	9.0	297	0.7342	0.7342	0.7706	-1.1938	0.2703
No log	10.0	330	0.7342	0.7342	0.7706	-1.1938	0.2703
No log	11.0	363	0.7342	0.7342	0.7706	-1.1938	0.2703
No log	12.0	396	0.7342	0.7342	0.7706	-1.1938	0.2703
No log	13.0	429	0.7342	0.7342	0.7706	-1.1938	0.2703
No log	14.0	462	0.7342	0.7342	0.7706	-1.1938	0.2703
No log	15.0	495	0.7342	0.7342	0.7706	-1.1938	0.2703

Framework versions

• Transformers 4.28.1
• Pytorch 2.0.0+cu118
• Datasets 2.12.0
• Tokenizers 0.13.3