diaster_distilbert_base_uncased

nixtasy/diaster_distilbert_base_uncased

diaster_distilbert_base_uncased is a text classification model from nixtasy. 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

12% of all-time downloads

All-time downloads

Public

Repo size

1.6 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin268 MB · 100%

At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: distilbert
Access: Public
Created: May 26, 2023
Updated: May 26, 2023
SHA: ab1f47db

Try a prompt

Model card

From the Hugging Face model README

diaster_distilbert_base_uncased

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

Loss: 1.0345
Accuracy: 0.8076

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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	381	0.3926	0.8372
0.4214	2.0	762	0.4764	0.8234
0.3014	3.0	1143	0.4208	0.8352
0.2051	4.0	1524	0.5139	0.8280
0.2051	5.0	1905	0.8480	0.7840
0.1424	6.0	2286	0.8045	0.8155
0.1042	7.0	2667	0.9295	0.8188
0.075	8.0	3048	0.9241	0.8142
0.075	9.0	3429	1.0063	0.8083
0.0614	10.0	3810	1.0345	0.8076

Framework versions

Transformers 4.28.0
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3

Task: Text Classification
Library: transformers
Type: distilbert
License: apache-2.0
Created: May 26, 2023
Updated: May 26, 2023