task-t2

This model is a fine-tuned version of KpRT/task-t1 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.3666
• F1: 0.7591
• Chronic Disease F1: 0.7643
• Chronic Disease Num: 2090
• Cancer F1: 0.6815
• Cancer Num: 896
• Allergy F1: 0.7304
• Allergy Num: 200
• Treatment F1: 0.7803
• Treatment Num: 3185
• Other F1: 0
• Other Num: 0

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: 2

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Chronic Disease F1	Chronic Disease Num	Cancer F1	Cancer Num	Allergy F1	Allergy Num	Treatment F1	Treatment Num	Other F1	Other Num
0.4565	0.3049	100	0.4226	0.7177	0.7053	2090	0.6397	896	0.6633	200	0.7524	3185	0	0
0.4055	0.6098	200	0.3888	0.7396	0.7399	2090	0.6684	896	0.5989	200	0.7673	3185	0	0
0.4327	0.9146	300	0.3818	0.7441	0.7441	2090	0.6614	896	0.7506	200	0.7684	3185	0	0
0.3348	1.2195	400	0.3783	0.7518	0.7459	2090	0.6825	896	0.7032	200	0.7778	3185	0	0
0.3207	1.5244	500	0.3701	0.7597	0.7619	2090	0.6830	896	0.7457	200	0.7825	3185	0	0
0.3224	1.8293	600	0.3666	0.7591	0.7643	2090	0.6815	896	0.7304	200	0.7803	3185	0	0

Framework versions

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