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: 0.2391
F1: 0.5650
Roc Auc: 0.7487
Accuracy: 0.1228

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: 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: 15

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
No log	1.0	50	0.3095	0.1123	0.5442	0.0351
No log	2.0	100	0.2862	0.2744	0.6015	0.0702
No log	3.0	150	0.2642	0.3740	0.6488	0.0877
No log	4.0	200	0.2563	0.4429	0.6792	0.0526
No log	5.0	250	0.2492	0.5030	0.7178	0.0877
No log	6.0	300	0.2323	0.5296	0.7199	0.1228
No log	7.0	350	0.2372	0.5433	0.7326	0.1053
No log	8.0	400	0.2326	0.5371	0.7279	0.1053
No log	9.0	450	0.2346	0.5587	0.7382	0.1404
0.1673	10.0	500	0.2393	0.5819	0.7534	0.1053
0.1673	11.0	550	0.2370	0.5656	0.7471	0.1053
0.1673	12.0	600	0.2374	0.5680	0.7479	0.1404
0.1673	13.0	650	0.2392	0.5680	0.7500	0.1228
0.1673	14.0	700	0.2398	0.5650	0.7487	0.1228
0.1673	15.0	750	0.2391	0.5650	0.7487	0.1228

Framework versions

Transformers 4.38.1
Pytorch 2.1.2
Datasets 2.1.0
Tokenizers 0.15.2

krittapas/my-clf

my-clf

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

krittapas/
my-clf