distilbert-base-cased

xshubhamx/distilbert-base-cased

distilbert-base-cased 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: distilbert
Access: Public
Created: Apr 11, 2024
Updated: Apr 13, 2024
SHA: 940aaecc

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Model card

From the Hugging Face model README

distilbert-base-cased

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

Loss: 1.7353
Accuracy: 0.8033
Precision: 0.8036
Recall: 0.8033
Precision Macro: 0.7607
Recall Macro: 0.7462
Macro Fpr: 0.0178
Weighted Fpr: 0.0172
Weighted Specificity: 0.9733
Macro Specificity: 0.9851
Weighted Sensitivity: 0.8033
Macro Sensitivity: 0.7462
F1 Micro: 0.8033
F1 Macro: 0.7497
F1 Weighted: 0.8026

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
1.3432	1.0	643	1.0505	0.6785	0.6416	0.6785	0.4669	0.4706	0.0350	0.0327	0.9402	0.9746	0.6785	0.4706	0.6785	0.4509	0.6411
0.7893	2.0	1286	0.7761	0.7568	0.7644	0.7568	0.6700	0.6863	0.0227	0.0224	0.9710	0.9819	0.7568	0.6863	0.7568	0.6741	0.7570
0.591	3.0	1929	0.7662	0.7971	0.7950	0.7971	0.6923	0.7036	0.0184	0.0179	0.9734	0.9847	0.7971	0.7036	0.7971	0.6924	0.7940
0.3172	4.0	2572	0.9908	0.7847	0.7920	0.7847	0.7002	0.7114	0.0197	0.0192	0.9734	0.9839	0.7847	0.7114	0.7847	0.6965	0.7836
0.2327	5.0	3215	1.0959	0.8025	0.8055	0.8025	0.7796	0.7458	0.0180	0.0173	0.9729	0.9850	0.8025	0.7458	0.8025	0.7542	0.8003
0.1287	6.0	3858	1.3398	0.7823	0.7939	0.7823	0.7423	0.7445	0.0198	0.0195	0.9728	0.9837	0.7823	0.7445	0.7823	0.7378	0.7845
0.0781	7.0	4501	1.3660	0.8040	0.8089	0.8040	0.7498	0.7358	0.0177	0.0171	0.9725	0.9851	0.8040	0.7358	0.8040	0.7395	0.8052
0.0418	8.0	5144	1.5433	0.7932	0.8035	0.7932	0.7745	0.7476	0.0187	0.0183	0.9722	0.9844	0.7932	0.7476	0.7932	0.7522	0.7953
0.0348	9.0	5787	1.4788	0.8002	0.8076	0.8002	0.7552	0.7622	0.0179	0.0175	0.9754	0.9850	0.8002	0.7622	0.8002	0.7551	0.8021
0.0151	10.0	6430	1.6028	0.8087	0.8125	0.8087	0.7872	0.7454	0.0172	0.0166	0.9731	0.9854	0.8087	0.7454	0.8087	0.7566	0.8083
0.0101	11.0	7073	1.6394	0.8056	0.8065	0.8056	0.7595	0.7523	0.0176	0.0169	0.9737	0.9853	0.8056	0.7523	0.8056	0.7530	0.8052
0.0064	12.0	7716	1.7666	0.7916	0.7984	0.7916	0.7482	0.7439	0.0190	0.0185	0.9729	0.9843	0.7916	0.7439	0.7916	0.7427	0.7923
0.0028	13.0	8359	1.7160	0.8040	0.8077	0.8040	0.7694	0.7739	0.0177	0.0171	0.9739	0.9852	0.8040	0.7739	0.8040	0.7690	0.8049
0.002	14.0	9002	1.7221	0.8040	0.8066	0.8040	0.7630	0.7490	0.0177	0.0171	0.9734	0.9852	0.8040	0.7490	0.8040	0.7520	0.8042
0.0019	15.0	9645	1.7353	0.8033	0.8036	0.8033	0.7607	0.7462	0.0178	0.0172	0.9733	0.9851	0.8033	0.7462	0.8033	0.7497	0.8026

Framework versions

Transformers 4.38.2
Pytorch 2.1.2
Datasets 2.1.0
Tokenizers 0.15.2

Task: Text Classification
Library: transformers
Type: distilbert
Created: Apr 11, 2024
Updated: Apr 13, 2024