This model is a fine-tuned version of avsolatorio/GIST-large-Embedding-v0 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0496
F1: 0.9557
Roc Auc: 0.9752
Accuracy: 0.8364

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: 5e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 13

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
No log	1.0	200	0.2353	0.2902	0.6136	0.0455
No log	2.0	400	0.1819	0.6613	0.8093	0.3182
0.2288	3.0	600	0.1185	0.7709	0.8520	0.4636
0.2288	4.0	800	0.0881	0.9505	0.9732	0.7545
0.0775	5.0	1000	0.0701	0.9504	0.9701	0.8091
0.0775	6.0	1200	0.0623	0.9557	0.9752	0.8364
0.0775	7.0	1400	0.0557	0.9557	0.9752	0.8364
0.0276	8.0	1600	0.0516	0.9557	0.9752	0.8364
0.0276	9.0	1800	0.0516	0.9570	0.9760	0.8545
0.0172	10.0	2000	0.0505	0.9570	0.9760	0.8545
0.0172	11.0	2200	0.0507	0.9557	0.9752	0.8364
0.0172	12.0	2400	0.0499	0.9557	0.9752	0.8364
0.0137	13.0	2600	0.0496	0.9557	0.9752	0.8364

Framework versions

Transformers 4.38.1
Pytorch 2.1.2
Datasets 2.1.0
Tokenizers 0.15.2

krittapas/my-clf22

my-clf22

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

krittapas/
my-clf22