legal_question_classification

SHONOSUKE/legal_question_classification

legal_question_classification is a text classification model from SHONOSUKE. 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. --

Downloads · 30 days

23% of all-time downloads

All-time downloads

Public

Repo size

4.4 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.pt2.7 GB · 60%

At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Dec 20, 2023
Updated: Dec 21, 2023
SHA: 942751d1

Try a prompt

Model card

From the Hugging Face model README

legal_question_classification

This model is a fine-tuned version of cl-tohoku/bert-base-japanese-v3 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.4890
Accuracy: 0.7948

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
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5286	1.0	582	0.4952	0.7948
0.4962	2.0	1164	0.4909	0.7948
0.4847	3.0	1746	0.4890	0.7948

Framework versions

Transformers 4.17.0
Pytorch 2.1.0+cu121
Tokenizers 0.15.0

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Dec 20, 2023
Updated: Dec 21, 2023