xlnet-base-cased_fold_5_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: 1.7395
• F1: 0.8206

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	288	0.4246	0.8154
0.4211	2.0	576	0.5181	0.8063
0.4211	3.0	864	0.4939	0.8149
0.2483	4.0	1152	0.6181	0.8227
0.2483	5.0	1440	0.9251	0.8006
0.1512	6.0	1728	0.9639	0.8082
0.0858	7.0	2016	1.1315	0.8074
0.0858	8.0	2304	1.1322	0.8303
0.053	9.0	2592	1.3171	0.8017
0.053	10.0	2880	1.3729	0.8100
0.0325	11.0	3168	1.2708	0.8252
0.0325	12.0	3456	1.5105	0.8242
0.0203	13.0	3744	1.4902	0.8233
0.0179	14.0	4032	1.5874	0.8194
0.0179	15.0	4320	1.5933	0.8135
0.0174	16.0	4608	1.5908	0.8088
0.0174	17.0	4896	1.5692	0.8249
0.0129	18.0	5184	1.6597	0.8167
0.0129	19.0	5472	1.6009	0.8218
0.0095	20.0	5760	1.6962	0.8225
0.0062	21.0	6048	1.7075	0.8182
0.0062	22.0	6336	1.7335	0.8181
0.0077	23.0	6624	1.7175	0.8204
0.0077	24.0	6912	1.7680	0.8187
0.0024	25.0	7200	1.7395	0.8206

Framework versions

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