2023_AI_HW_001

JessCatWu/2023_AI_HW_001

2023_AI_HW_001 is a text classification model from JessCatWu. 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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At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: distilbert
Access: Public
Created: Dec 23, 2023
Updated: Dec 23, 2023
SHA: 36c02eb6

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Base models

Model card

From the Hugging Face model README

2023_AI_HW_001

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.8709
Matthews Correlation: 0.5435

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	Matthews Correlation
0.5139	1.0	535	0.4551	0.4542
0.3388	2.0	1070	0.4634	0.5256
0.2334	3.0	1605	0.6328	0.5256
0.1635	4.0	2140	0.7833	0.5378
0.1169	5.0	2675	0.8709	0.5435

Framework versions

Transformers 4.36.2
Pytorch 2.1.0+cu121
Datasets 2.16.0
Tokenizers 0.15.0

Task: Text Classification
Library: transformers
Type: distilbert
License: apache-2.0
Created: Dec 23, 2023
Updated: Dec 23, 2023