xlnet-base-cased_fold_4_binary_v1

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

• Loss: 1.5724
• F1: 0.8315

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 25

Training results

Training Loss	Epoch	Step	Validation Loss	F1
No log	1.0	289	0.4043	0.8009
0.4373	2.0	578	0.4093	0.8260
0.4373	3.0	867	0.5084	0.8206
0.2707	4.0	1156	0.5945	0.8087
0.2707	5.0	1445	0.6389	0.8251
0.1691	6.0	1734	0.8131	0.8156
0.1012	7.0	2023	0.9865	0.8190
0.1012	8.0	2312	1.1356	0.8342
0.0506	9.0	2601	1.0624	0.8369
0.0506	10.0	2890	1.2604	0.8255
0.0384	11.0	3179	1.2648	0.8183
0.0384	12.0	3468	1.3763	0.8158
0.0318	13.0	3757	1.4966	0.8217
0.0221	14.0	4046	1.3889	0.8250
0.0221	15.0	4335	1.4014	0.8284
0.0145	16.0	4624	1.5321	0.8289
0.0145	17.0	4913	1.4914	0.8233
0.0172	18.0	5202	1.3946	0.8314
0.0172	19.0	5491	1.5032	0.8269
0.0135	20.0	5780	1.5111	0.8328
0.0087	21.0	6069	1.4899	0.8318
0.0087	22.0	6358	1.5562	0.8311
0.0061	23.0	6647	1.5384	0.8327
0.0061	24.0	6936	1.5798	0.8304
0.0052	25.0	7225	1.5724	0.8315

Framework versions

• Transformers 4.21.1
• Pytorch 1.12.0+cu113
• Datasets 2.4.0
• Tokenizers 0.12.1