roberta-base

xshubhamx/roberta-base

roberta-base is a text classification model from xshubhamx. 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: roberta
Access: Public
Created: Apr 11, 2024
Updated: Apr 14, 2024
SHA: 03bdc492

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Model card

From the Hugging Face model README

roberta-base

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.3682
Accuracy: 0.8280
Precision: 0.8277
Recall: 0.8280
Precision Macro: 0.7620
Recall Macro: 0.7780
Macro Fpr: 0.0163
Weighted Fpr: 0.0158
Weighted Specificity: 0.9771
Macro Specificity: 0.9862
Weighted Sensitivity: 0.8164
Macro Sensitivity: 0.7780
F1 Micro: 0.8164
F1 Macro: 0.7665
F1 Weighted: 0.8173

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
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	Precision Macro	Recall Macro	Macro Fpr	Weighted Fpr	Weighted Specificity	Macro Specificity	Weighted Sensitivity	Macro Sensitivity	F1 Micro	F1 Macro	F1 Weighted
1.4921	1.0	643	1.0307	0.6762	0.6362	0.6762	0.3746	0.4027	0.0351	0.0331	0.9438	0.9747	0.6762	0.4027	0.6762	0.3676	0.6382
0.9019	2.0	1286	0.8136	0.7374	0.7158	0.7374	0.4625	0.5149	0.0251	0.0248	0.9701	0.9805	0.7374	0.5149	0.7374	0.4767	0.7197
0.7714	3.0	1929	0.8494	0.7622	0.7386	0.7622	0.5056	0.5354	0.0224	0.0218	0.9713	0.9822	0.7622	0.5354	0.7622	0.5064	0.7441
0.5351	4.0	2572	0.9905	0.7645	0.7657	0.7645	0.5496	0.5653	0.0224	0.0215	0.9673	0.9821	0.7645	0.5653	0.7645	0.5444	0.7546
0.4521	5.0	3215	1.0260	0.7901	0.7882	0.7901	0.6421	0.6315	0.0190	0.0186	0.9745	0.9843	0.7901	0.6315	0.7901	0.6117	0.7794
0.3466	6.0	3858	1.0385	0.7870	0.8134	0.7870	0.6722	0.6335	0.0192	0.0190	0.9777	0.9843	0.7870	0.6335	0.7870	0.6119	0.7890
0.2333	7.0	4501	1.1465	0.8118	0.8064	0.8118	0.6795	0.6784	0.0169	0.0163	0.9746	0.9858	0.8118	0.6784	0.8118	0.6657	0.8058
0.1658	8.0	5144	1.2419	0.8149	0.8149	0.8149	0.7319	0.7440	0.0165	0.0160	0.9771	0.9861	0.8149	0.7440	0.8149	0.7329	0.8121
0.1597	9.0	5787	1.3441	0.8180	0.8259	0.8180	0.8314	0.7702	0.0160	0.0156	0.9768	0.9863	0.8180	0.7702	0.8180	0.7804	0.8190
0.11	10.0	6430	1.3505	0.8025	0.8152	0.8025	0.7520	0.7654	0.0178	0.0173	0.9761	0.9852	0.8025	0.7654	0.8025	0.7500	0.8065
0.0747	11.0	7073	1.3682	0.8280	0.8277	0.8280	0.8096	0.7820	0.0152	0.0146	0.9761	0.9869	0.8280	0.7820	0.8280	0.7850	0.8253
0.0519	12.0	7716	1.4437	0.8164	0.8188	0.8164	0.7731	0.7751	0.0164	0.0158	0.9755	0.9861	0.8164	0.7751	0.8164	0.7699	0.8170
0.0324	13.0	8359	1.4511	0.8087	0.8127	0.8087	0.7552	0.7802	0.0171	0.0166	0.9769	0.9857	0.8087	0.7802	0.8087	0.7638	0.8097
0.0184	14.0	9002	1.5005	0.8141	0.8196	0.8141	0.7613	0.7848	0.0165	0.0160	0.9776	0.9861	0.8141	0.7848	0.8141	0.7681	0.8159
0.0137	15.0	9645	1.4995	0.8164	0.8193	0.8164	0.7620	0.7780	0.0163	0.0158	0.9771	0.9862	0.8164	0.7780	0.8164	0.7665	0.8173

Framework versions

Transformers 4.38.2
Pytorch 2.1.2
Datasets 2.1.0
Tokenizers 0.15.2

Task: Text Classification
Library: transformers
Type: roberta
Created: Apr 11, 2024
Updated: Apr 14, 2024