distilbert-base-uncased-finetuned-mnli

omriuz/distilbert-base-uncased-finetuned-mnli

distilbert-base-uncased-finetuned-mnli is a text classification model from omriuz. 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

452

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: Aug 5, 2022
Updated: Aug 6, 2022
SHA: 4e99caed

Try a prompt

Model card

From the Hugging Face model README

distilbert-base-uncased-finetuned-mnli

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: 0.8311
Accuracy: 0.6574

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: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.8687	1.0	2636	0.8341	0.6495
0.7788	2.0	5272	0.8311	0.6574

Framework versions

Transformers 4.21.1
Pytorch 1.12.0+cu113
Datasets 2.4.0
Tokenizers 0.12.1

Task: Text Classification
Library: transformers
Type: distilbert
License: apache-2.0
Created: Aug 5, 2022
Updated: Aug 6, 2022