Improved-Arabert-twitter-sentiment-No-dropout

Anwaarma/Improved-Arabert-twitter-sentiment-No-dropout

Improved-Arabert-twitter-sentiment-No-dropout is a text classification model from Anwaarma. Use it when you need a label for a piece of text. It is set up for transformers.

should probably proofread and complete it, then remove this comment. --

Downloads · 30 days

7% of all-time downloads

All-time downloads

129

Public

Repo size

2.2 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin541 MB · 100%

At a glance

Task: Text Classification
Library: transformers
Model type: bert
Access: Public
Created: Nov 19, 2023
Updated: Nov 19, 2023
SHA: 7b9addb4

Try a prompt

Base models

aubmindlab/bert-base-arabertv2

Model card

From the Hugging Face model README

Improved-Arabert-twitter-sentiment-No-dropout

This model is a fine-tuned version of aubmindlab/bert-base-arabertv2 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.5434
Accuracy: 0.9

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: 1e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5764	0.55	50	0.4925	0.79
0.3357	1.1	100	0.3094	0.88
0.2183	1.65	150	0.2971	0.87
0.2042	2.2	200	0.3013	0.89
0.1258	2.75	250	0.3038	0.9
0.1359	3.3	300	0.3114	0.89
0.0893	3.85	350	0.3108	0.91
0.0816	4.4	400	0.3569	0.9
0.071	4.95	450	0.3574	0.9
0.1043	5.49	500	0.4332	0.89
0.0407	6.04	550	0.4232	0.9
0.0378	6.59	600	0.4273	0.91
0.0341	7.14	650	0.4671	0.91
0.0226	7.69	700	0.5174	0.9
0.0215	8.24	750	0.4786	0.89
0.0329	8.79	800	0.4853	0.9
0.021	9.34	850	0.5430	0.9
0.0219	9.89	900	0.5510	0.89
0.0154	10.44	950	0.5518	0.9
0.0119	10.99	1000	0.5473	0.9
0.0108	11.54	1050	0.5285	0.9
0.0138	12.09	1100	0.5239	0.91
0.0133	12.64	1150	0.5584	0.89
0.0121	13.19	1200	0.5334	0.9
0.0063	13.74	1250	0.5325	0.91
0.0061	14.29	1300	0.5429	0.9
0.0105	14.84	1350	0.5434	0.9

Framework versions

Transformers 4.34.1
Pytorch 2.1.0+cu118
Datasets 2.14.7
Tokenizers 0.14.1

Task: Text Classification
Library: transformers
Type: bert
Created: Nov 19, 2023
Updated: Nov 19, 2023