Log-Analysis-Model-DistilBert

OMEGAMAX10/Log-Analysis-Model-DistilBert

Log-Analysis-Model-DistilBert is a text classification model from OMEGAMAX10. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: distilbert
Access: Public
Created: Mar 30, 2024
Updated: Mar 30, 2024
SHA: 3bdc4179

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Base models

Model card

From the Hugging Face model README

Log-Analysis-Model-DistilBert

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

Loss: 0.0454

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: 5

Training results

Training Loss	Epoch	Step	Validation Loss
0.0635	0.1	500	0.0563
0.0523	0.2	1000	0.0571
0.0462	0.29	1500	0.0600
0.0398	0.39	2000	0.0618
0.0456	0.49	2500	0.0593
0.0799	0.59	3000	0.0579
0.0823	0.69	3500	0.0595
0.061	0.79	4000	0.0751
0.0486	0.88	4500	0.0555
0.065	0.98	5000	0.0584
0.0553	1.08	5500	0.0562
0.051	1.18	6000	0.0564
0.0698	1.28	6500	0.0537
0.0556	1.37	7000	0.0498
0.059	1.47	7500	0.0571
0.0556	1.57	8000	0.0514
0.0503	1.67	8500	0.0571
0.0629	1.77	9000	0.0515
0.041	1.87	9500	0.0551
0.0465	1.96	10000	0.0593
0.0523	2.06	10500	0.0540
0.0511	2.16	11000	0.0552
0.0633	2.26	11500	0.0530
0.0487	2.36	12000	0.0477
0.05	2.46	12500	0.0494
0.0536	2.55	13000	0.0483
0.0313	2.65	13500	0.0508
0.0533	2.75	14000	0.0502
0.0419	2.85	14500	0.0509
0.0298	2.95	15000	0.0556
0.0554	3.04	15500	0.0504
0.0568	3.14	16000	0.0473
0.052	3.24	16500	0.0525
0.0342	3.34	17000	0.0531
0.0519	3.44	17500	0.0485
0.0354	3.54	18000	0.0529
0.0539	3.63	18500	0.0489
0.0381	3.73	19000	0.0466
0.0392	3.83	19500	0.0480
0.0571	3.93	20000	0.0458
0.0314	4.03	20500	0.0475
0.0357	4.12	21000	0.0480
0.0607	4.22	21500	0.0454
0.0339	4.32	22000	0.0466
0.033	4.42	22500	0.0480
0.0524	4.52	23000	0.0465
0.0431	4.62	23500	0.0467
0.0521	4.71	24000	0.0459
0.039	4.81	24500	0.0464
0.0333	4.91	25000	0.0466

Framework versions

Transformers 4.33.0
Pytorch 2.2.0+cu118
Datasets 2.16.1
Tokenizers 0.13.3

Task: Text Classification
Library: transformers
Type: distilbert
License: apache-2.0
Created: Mar 30, 2024
Updated: Mar 30, 2024