tweet_sentiments_analysis_distilbert-base-uncased

Junr-syl/tweet_sentiments_analysis_distilbert-base-uncased

tweet_sentiments_analysis_distilbert-base-uncased is a text classification model from Junr-syl. 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

361

Public

Repo size

2.1 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: Jul 19, 2023
Updated: Jul 19, 2023
SHA: 98672c33

Try a prompt

Base models

Model card

From the Hugging Face model README

tweet_sentiments_analysis_distilbert-base-uncased

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: 1.1715
F1: 0.7180

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: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 7

Training results

Training Loss	Epoch	Step	Validation Loss	F1
0.7542	1.0	1000	0.7429	0.6630
0.7264	2.0	2000	0.7214	0.6782
0.6376	3.0	3000	0.6610	0.7171
0.5196	4.0	4000	0.7578	0.7291
0.4344	5.0	5000	0.8670	0.7248
0.3342	6.0	6000	1.0522	0.7223
0.2841	7.0	7000	1.1715	0.7180

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3

Task: Text Classification
Library: transformers
Type: distilbert
License: apache-2.0
Created: Jul 19, 2023
Updated: Jul 19, 2023