OTE-NoDapt-ABSA-bert-base-MARBERTv2-DefultHp-FineTune – AI Model by salohnana2018 | AlphaNeural AI

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salohnana2018/
OTE-NoDapt-ABSA-bert-base-MARBERTv2-DefultHp-FineTune

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token-classification

generated_from_trainer

UBC-NLP/MARBERTv2

autotrain_compatible

endpoints_compatible

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OTE-NoDapt-ABSA-bert-base-MARBERTv2-DefultHp-FineTune

This model is a fine-tuned version of UBC-NLP/MARBERTv2 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.1711
Precision: 0.7538
Recall: 0.7902
F1: 0.7716
Accuracy: 0.9536

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: 32
eval_batch_size: 8
seed: 25
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.1914	1.0	121	0.1169	0.7655	0.7369	0.7510	0.9536
0.0946	2.0	242	0.1192	0.7952	0.7334	0.7631	0.9558
0.0643	3.0	363	0.1336	0.7471	0.7932	0.7695	0.9537
0.0428	4.0	484	0.1585	0.7312	0.7957	0.7621	0.9517
0.0286	5.0	605	0.1711	0.7538	0.7902	0.7716	0.9536

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.14.3
Tokenizers 0.13.3