OTE-NoDapt-ABSA-bert-base-qarib-OrginalHP-FineTune

salohnana2018/OTE-NoDapt-ABSA-bert-base-qarib-OrginalHP-FineTune

OTE-NoDapt-ABSA-bert-base-qarib-OrginalHP-FineTune is a token classification model from salohnana2018. Use it when you need labels on individual words, such as names. It is set up for transformers.

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

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At a glance

Task: Token Classification
Library: transformers
Model type: bert
Access: Public
Created: Aug 9, 2023
Updated: Aug 9, 2023
SHA: fef291b9

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Base models

Model card

From the Hugging Face model README

OTE-NoDapt-ABSA-bert-base-qarib-OrginalHP-FineTune

This model is a fine-tuned version of qarib/bert-base-qarib on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.1348
Precision: 0.7488
Recall: 0.7723
F1: 0.7604
Accuracy: 0.9532

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: 8e-05
train_batch_size: 64
eval_batch_size: 8
seed: 25
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.1656	1.0	61	0.1196	0.7299	0.7932	0.7603	0.9528
0.08	2.0	122	0.1176	0.7561	0.7678	0.7619	0.9543
0.0501	3.0	183	0.1348	0.7488	0.7723	0.7604	0.9532

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3

Task: Token Classification
Library: transformers
Type: bert
Created: Aug 9, 2023
Updated: Aug 9, 2023