ES-ENG-mDeBERTa-sentiment

MinaAlmasi/ES-ENG-mDeBERTa-sentiment

ES-ENG-mDeBERTa-sentiment is a text classification model from MinaAlmasi. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as cc-by-nc-4.0.

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

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At a glance

Task: Text Classification
Library: transformers
License: cc-by-nc-4.0
Model type: deberta-v2
Access: Public
Created: May 19, 2023
Updated: May 22, 2023
SHA: 39ebc6d2

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Model card

From the Hugging Face model README

ES-ENG-mDeBERTa-sentiment

This model is a fine-tuned version of microsoft/mdeberta-v3-base on a Custom dataset.

The best model (stopped after 20 epochs) achieves the following results on the evaluation set:

Loss:0.7549
Accuracy: 0.6806
F1: 0.6783
Precision: 0.6775
Recall: 0.6806

Intended uses & limitations

Note that commercial use with this model is prohibited.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 2e-06
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
1.0833	1.0	208	1.0218	0.3835	0.2413	0.4619	0.3835
0.9826	2.0	416	0.9220	0.5673	0.5524	0.5583	0.5673
0.8951	3.0	624	0.8435	0.5916	0.5836	0.5853	0.5916
0.8377	4.0	832	0.8200	0.5994	0.5916	0.5931	0.5994
0.8083	5.0	1040	0.8110	0.5977	0.5960	0.5957	0.5977
0.7854	6.0	1248	0.8009	0.5994	0.5943	0.5916	0.5994
0.7699	7.0	1456	0.7919	0.6084	0.6065	0.6055	0.6084
0.7489	8.0	1664	0.7827	0.6230	0.6164	0.6192	0.6230
0.7323	9.0	1872	0.7739	0.6272	0.6251	0.6246	0.6272
0.7162	10.0	2080	0.7725	0.6408	0.6332	0.6351	0.6408
0.6958	11.0	2288	0.7636	0.6414	0.6393	0.6383	0.6414
0.6816	12.0	2496	0.7582	0.6495	0.6491	0.6516	0.6495
0.6706	13.0	2704	0.7492	0.6628	0.6607	0.6595	0.6628
0.6569	14.0	2912	0.7554	0.6586	0.6580	0.6579	0.6586
0.6422	15.0	3120	0.7525	0.6676	0.6661	0.6667	0.6676
0.6408	16.0	3328	0.7527	0.6660	0.6658	0.6669	0.6660
0.6273	17.0	3536	0.7483	0.6712	0.6700	0.6710	0.6712
0.6186	18.0	3744	0.7531	0.6748	0.6731	0.6727	0.6748
0.6107	19.0	3952	0.7482	0.6799	0.6786	0.6782	0.6799
0.6055	20.0	4160	0.7549	0.6806	0.6783	0.6775	0.6806
0.6026	21.0	4368	0.7574	0.6725	0.6719	0.6733	0.6725
0.5906	22.0	4576	0.7587	0.6728	0.6721	0.6723	0.6728
0.5888	23.0	4784	0.7621	0.6761	0.6756	0.6758	0.6761

Framework versions

Transformers 4.29.2
Pytorch 2.0.1+cu117
Datasets 2.12.0
Tokenizers 0.13.3

Task: Text Classification
Library: transformers
Type: deberta-v2
License: cc-by-nc-4.0
Created: May 19, 2023
Updated: May 22, 2023