results

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

• Loss: 0.6801

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: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss
0.5048	1.0	208	0.4436
0.3539	2.0	416	0.5064
0.2982	3.0	624	0.4879
0.2457	4.0	832	0.4303
0.1879	5.0	1040	0.5073
0.1542	6.0	1248	0.5062
0.1273	7.0	1456	0.6459
0.1017	8.0	1664	0.7306
0.0919	9.0	1872	0.6311
0.0821	10.0	2080	0.6049
0.0752	11.0	2288	0.8128
0.0629	12.0	2496	0.6608
0.0609	13.0	2704	0.7059
0.0555	14.0	2912	0.6801

Framework versions

• Transformers 4.42.4
• Pytorch 2.3.1+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1