my-clf-microsoft

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: 0.2194
F1: 0.6392
Roc Auc: 0.7794
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	0.3035	0.1236	0.5447	0.0
No log	2.0	100	0.2696	0.3655	0.6420	0.0877
No log	3.0	150	0.2468	0.3611	0.6390	0.0877
No log	4.0	200	0.2387	0.4837	0.6999	0.0877
No log	5.0	250	0.2311	0.5244	0.7164	0.0526
No log	6.0	300	0.2215	0.5768	0.7326	0.1053
No log	7.0	350	0.2242	0.6033	0.7593	0.0877
No log	8.0	400	0.2155	0.6350	0.7624	0.0877
No log	9.0	450	0.2227	0.6294	0.7746	0.1228
0.1644	10.0	500	0.2156	0.6412	0.7772	0.1053
0.1644	11.0	550	0.2176	0.6332	0.7715	0.1053
0.1644	12.0	600	0.2182	0.6430	0.7816	0.1228
0.1644	13.0	650	0.2190	0.6390	0.7794	0.1228
0.1644	14.0	700	0.2184	0.6377	0.7788	0.1228
0.1644	15.0	750	0.2194	0.6392	0.7794	0.1228

Framework versions

Transformers 4.38.1
Pytorch 2.1.2
Datasets 2.1.0
Tokenizers 0.15.2

krittapas
/

my-clf-microsoft

my-clf-microsoft

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Model tree for krittapas/my-clf-microsoft

Evaluation results