ICU_Returns_Gatortron

This model is a fine-tuned version of UFNLP/gatortron-base on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.7852
• F1:: 0.7203
• Roc Auc: 0.7335
• Precision with 0:: 0.9126
• Precision with 1:: 0.6628
• Recall with 0:: 0.5165
• Recal with 1:: 0.9505
• Accuracy:: 0.7335

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: 0.0001
• train_batch_size: 32
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	F1:	Roc Auc	Precision with 0:	Precision with 1:	Recall with 0:	Recal with 1:	Accuracy:
No log	1.0	46	0.6889	0.6965	0.7115	0.8812	0.6464	0.4890	0.9341	0.7115
No log	2.0	92	0.7628	0.7287	0.7390	0.8919	0.6719	0.5440	0.9341	0.7390
No log	3.0	138	1.8927	0.6372	0.6703	0.9306	0.6062	0.3681	0.9725	0.6703
No log	4.0	184	1.7208	0.7236	0.7363	0.9135	0.6654	0.5220	0.9505	0.7363
No log	5.0	230	1.7852	0.7203	0.7335	0.9126	0.6628	0.5165	0.9505	0.7335

Framework versions

• Transformers 4.34.0
• Pytorch 2.1.0+cu121
• Datasets 2.14.5
• Tokenizers 0.14.1