distilbert-base-uncased-finetuned-sst2-nostop

DioLiu/distilbert-base-uncased-finetuned-sst2-nostop

distilbert-base-uncased-finetuned-sst2-nostop is a text classification model from DioLiu. 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

2% of all-time downloads

All-time downloads

493

Public

Repo size

1.1 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin263 MB · 100%

At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: distilbert
Access: Public
Created: May 3, 2022
Updated: May 3, 2022
SHA: 0fece57f

Try a prompt

Model card

From the Hugging Face model README

distilbert-base-uncased-finetuned-sst2-nostop

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: 0.0701
Accuracy: 0.9888

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
0.125	1.0	1116	0.0975	0.9743
0.0599	2.0	2232	0.0692	0.9840
0.0191	3.0	3348	0.0570	0.9871
0.0109	4.0	4464	0.0660	0.9882
0.0092	5.0	5580	0.0701	0.9888

Framework versions

Transformers 4.18.0
Pytorch 1.11.0+cu113
Datasets 2.1.0
Tokenizers 0.12.1

Task: Text Classification
Library: transformers
Type: distilbert
License: apache-2.0
Created: May 3, 2022
Updated: May 3, 2022