bert-base-uncased-amazon-massive-intent

cartesinus/bert-base-uncased-amazon-massive-intent

bert-base-uncased-amazon-massive-intent is a text classification model from cartesinus. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.

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

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Base models

Datasets

AmazonScience/massive

Model card

From the Hugging Face model README

bert-base-uncased-amazon-massive-intent

This model is a fine-tuned version of bert-base-uncased on Amazon Massive dataset (only en-US subset). It achieves the following results on the evaluation set:

Loss: 0.4897
Accuracy: 0.8903
F1: 0.8903

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: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
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	Accuracy	F1
2.5862	1.0	720	1.0160	0.8096	0.8096
1.0591	2.0	1440	0.6003	0.8716	0.8716
0.4151	3.0	2160	0.5113	0.8859	0.8859
0.3028	4.0	2880	0.5030	0.8883	0.8883
0.1852	5.0	3600	0.4897	0.8903	0.8903

Framework versions

Transformers 4.22.1
Pytorch 1.12.1+cu113
Datasets 2.5.1
Tokenizers 0.12.1

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Languages: en
Created: Sep 23, 2022
Updated: Sep 13, 2023