S02-PC

Anwaarma/S02-PC

S02-PC is a text classification model from Anwaarma. Use it when you need a label for a piece of text. It is set up for transformers.

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

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At a glance

Task: Text Classification
Library: transformers
Model type: bert
Access: Public
Created: Dec 24, 2023
Updated: Dec 24, 2023
SHA: e1eafc40

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Base models

Anwaarma/Merged-Server-praj

Model card

From the Hugging Face model README

S02-PC

This model is a fine-tuned version of Anwaarma/Merged-Server-praj on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.5986
Accuracy: 0.78
F1: 0.8764

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: 3e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	0.0	50	0.5686	0.6	0.5981
No log	0.01	100	0.5715	0.62	0.6205
No log	0.01	150	0.5591	0.64	0.6400
No log	0.01	200	0.5670	0.63	0.6288
No log	0.02	250	0.5568	0.61	0.6106
No log	0.02	300	0.5761	0.64	0.6383
No log	0.02	350	0.5515	0.61	0.6106
No log	0.03	400	0.5567	0.61	0.6087
No log	0.03	450	0.5590	0.62	0.6192
0.606	0.03	500	0.5454	0.64	0.6404
0.606	0.04	550	0.5509	0.63	0.6303
0.606	0.04	600	0.5451	0.64	0.6393
0.606	0.04	650	0.5461	0.65	0.6488
0.606	0.05	700	0.5443	0.62	0.6192
0.606	0.05	750	0.5461	0.66	0.6593
0.606	0.05	800	0.5420	0.66	0.6604
0.606	0.06	850	0.5414	0.65	0.6502
0.606	0.06	900	0.5411	0.65	0.6505
0.606	0.06	950	0.5413	0.69	0.6834
0.584	0.07	1000	0.5432	0.64	0.6353
0.584	0.07	1050	0.5335	0.64	0.6383
0.584	0.07	1100	0.5483	0.67	0.6702
0.584	0.08	1150	0.5548	0.66	0.6605
0.584	0.08	1200	0.5590	0.63	0.6306
0.584	0.09	1250	0.5580	0.67	0.6697
0.584	0.09	1300	0.5616	0.65	0.6502
0.584	0.09	1350	0.5620	0.62	0.6131
0.584	0.1	1400	0.5509	0.61	0.6059
0.584	0.1	1450	0.5473	0.66	0.6605
0.573	0.1	1500	0.5497	0.66	0.6593
0.573	0.11	1550	0.5450	0.65	0.6502
0.573	0.11	1600	0.5484	0.67	0.6689
0.573	0.11	1650	0.5398	0.66	0.6584
0.573	0.12	1700	0.5350	0.65	0.6477
0.573	0.12	1750	0.5333	0.64	0.6370
0.573	0.12	1800	0.5635	0.64	0.6400
0.573	0.13	1850	0.5742	0.63	0.6297

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.16.0
Tokenizers 0.15.0

Task: Text Classification
Library: transformers
Type: bert
Created: Dec 24, 2023
Updated: Dec 24, 2023