scideberta-cs-tdm-pretrained

This model is a fine-tuned version of KISTI-AI/scideberta-cs on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.8211
• Overall Precision: 0.6247
• Overall Recall: 0.7665
• Overall F1: 0.6884
• Overall Accuracy: 0.9288
• Datasetname F1: 0.6345
• Metricname F1: 0.8177
• Taskname F1: 0.6622

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: 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: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Overall Precision	Overall Recall	Overall F1	Overall Accuracy	Datasetname F1	Metricname F1	Taskname F1
No log	1.0	191	0.3160	0.4684	0.6953	0.5597	0.9187	0.5439	0.7008	0.5135
No log	2.0	382	0.3152	0.4370	0.6544	0.5240	0.9084	0.3623	0.7527	0.5303
0.4334	3.0	573	0.3713	0.4900	0.6768	0.5684	0.9116	0.5525	0.7692	0.5025
0.4334	4.0	764	0.4347	0.5554	0.6807	0.6117	0.9253	0.5943	0.7074	0.5795
0.4334	5.0	955	0.5098	0.5777	0.7309	0.6453	0.9258	0.6478	0.7902	0.5868
0.1097	6.0	1146	0.5453	0.5784	0.7401	0.6493	0.9265	0.5782	0.7642	0.6390
0.1097	7.0	1337	0.6200	0.6264	0.7586	0.6862	0.9349	0.6513	0.7826	0.6629
0.0499	8.0	1528	0.6072	0.6448	0.7401	0.6892	0.9380	0.6783	0.7935	0.6496
0.0499	9.0	1719	0.6568	0.6329	0.7414	0.6829	0.9347	0.6413	0.8086	0.6487
0.0499	10.0	1910	0.6726	0.6264	0.7520	0.6835	0.9312	0.6618	0.7967	0.6472
0.0247	11.0	2101	0.8104	0.6635	0.7282	0.6943	0.9395	0.6514	0.8159	0.6635
0.0247	12.0	2292	0.7022	0.6320	0.7704	0.6944	0.9376	0.6452	0.8122	0.6704
0.0247	13.0	2483	0.8143	0.6655	0.7216	0.6924	0.9366	0.6321	0.8122	0.6700
0.0176	14.0	2674	0.7723	0.6434	0.7309	0.6844	0.9329	0.6190	0.7934	0.6699
0.0176	15.0	2865	0.7726	0.6071	0.7480	0.6702	0.9320	0.6174	0.8122	0.6391
0.0132	16.0	3056	0.8124	0.6404	0.7493	0.6906	0.9329	0.6326	0.8098	0.6682
0.0132	17.0	3247	0.8269	0.6374	0.7467	0.6877	0.9336	0.6071	0.8268	0.6714
0.0132	18.0	3438	0.8826	0.6315	0.7573	0.6887	0.9343	0.6456	0.8142	0.6573
0.0125	19.0	3629	0.8602	0.6446	0.7467	0.6919	0.9320	0.6190	0.8156	0.6760
0.0125	20.0	3820	1.0048	0.6679	0.7216	0.6937	0.9350	0.6683	0.7932	0.6634
0.0093	21.0	4011	0.8211	0.6247	0.7665	0.6884	0.9288	0.6345	0.8177	0.6622

Framework versions

• Transformers 4.23.1
• Pytorch 1.12.1+cu102
• Datasets 2.6.1
• Tokenizers 0.13.1