distilbert-magazine-classifier

This model is a fine-tuned version of distilbert-base-cased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.8377
• Precision: 0.25
• Recall: 0.125
• Fscore: 0.1667

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-05
• 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: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	Fscore
0.1779	1.0	2	1.7584	0.2222	0.3333	0.2667
0.1635	2.0	4	1.7585	0.25	0.125	0.1667
0.1405	3.0	6	1.8377	0.25	0.125	0.1667

Framework versions

• Transformers 4.15.0
• Pytorch 1.10.0+cu111
• Datasets 1.17.0
• Tokenizers 0.10.3