multilabel_lora_distilbert_classifier_tuned_ru

pyteach237/multilabel_lora_distilbert_classifier_tuned_ru

multilabel_lora_distilbert_classifier_tuned_ru is a machine learning model from pyteach237. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.

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

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Hugging Face

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At a glance

Library: peft
License: apache-2.0
Access: Public
Created: Jul 8, 2024
Updated: Jul 8, 2024
SHA: ede5c6ba

Base models

Model card

From the Hugging Face model README

multilabel_lora_distilbert_classifier_tuned_ru

This model is a fine-tuned version of distilbert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.3658
Accuracy: 0.7845
F1: 0.7857
Precision: 0.7997
Recall: 0.7845

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: 4.993596574084884e-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: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
1.0622	1.0	727	0.9090	0.6025	0.5923	0.6149	0.6025
0.9449	2.0	1454	0.7451	0.6891	0.6855	0.6950	0.6891
0.7018	3.0	2181	0.6176	0.7359	0.7354	0.7377	0.7359
0.6192	4.0	2908	0.5854	0.7758	0.7751	0.7805	0.7758
0.4921	5.0	3635	0.5727	0.8061	0.8050	0.8202	0.8061
0.4091	6.0	4362	0.5019	0.8294	0.8293	0.8301	0.8294
0.3273	7.0	5089	0.4864	0.8404	0.8403	0.8409	0.8404
0.3473	8.0	5816	0.4828	0.8514	0.8512	0.8557	0.8514
0.2821	9.0	6543	0.4679	0.8597	0.8597	0.8597	0.8597
0.2599	10.0	7270	0.4874	0.8803	0.8799	0.8823	0.8803
0.2717	11.0	7997	0.4551	0.8831	0.8829	0.8832	0.8831
0.2211	12.0	8724	0.4602	0.8858	0.8856	0.8859	0.8858
0.2207	13.0	9451	0.5086	0.8845	0.8837	0.8862	0.8845
0.2166	14.0	10178	0.4795	0.8941	0.8936	0.8952	0.8941
0.1782	15.0	10905	0.4650	0.8955	0.8951	0.8959	0.8955

Framework versions

PEFT 0.11.1
Transformers 4.41.2
Pytorch 2.1.2
Datasets 2.19.2
Tokenizers 0.19.1

Library: peft
License: apache-2.0
Created: Jul 8, 2024
Updated: Jul 8, 2024