robust-arabert

Anwaarma/robust-arabert

robust-arabert 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. --

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At a glance

Task: Text Classification
Library: transformers
Model type: bert
Access: Public
Created: Jul 11, 2024
Updated: Jul 11, 2024
SHA: 0f562569

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Base models

Anwaarma/Improved-Arabert-twitter-sentiment2

Model card

From the Hugging Face model README

robust-arabert

This model is a fine-tuned version of Anwaarma/Improved-Arabert-twitter-sentiment2 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.2072
Accuracy: 0.94

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	0.0546	50	0.2677	0.91
No log	0.1092	100	0.2432	0.93
No log	0.1638	150	0.3328	0.91
No log	0.2183	200	0.2894	0.92
No log	0.2729	250	0.3008	0.91
No log	0.3275	300	0.1951	0.93
No log	0.3821	350	0.2176	0.94
No log	0.4367	400	0.2291	0.95
No log	0.4913	450	0.2678	0.93
0.2068	0.5459	500	0.2975	0.9
0.2068	0.6004	550	0.2245	0.92
0.2068	0.6550	600	0.2014	0.94
0.2068	0.7096	650	0.2189	0.93
0.2068	0.7642	700	0.2272	0.94
0.2068	0.8188	750	0.2148	0.92
0.2068	0.8734	800	0.2082	0.94
0.2068	0.9279	850	0.1869	0.93
0.2068	0.9825	900	0.2166	0.95
0.2068	1.0371	950	0.2095	0.94
0.1852	1.0917	1000	0.2948	0.92
0.1852	1.1463	1050	0.2586	0.93
0.1852	1.2009	1100	0.2669	0.93
0.1852	1.2555	1150	0.2635	0.94
0.1852	1.3100	1200	0.2600	0.94
0.1852	1.3646	1250	0.2290	0.95
0.1852	1.4192	1300	0.2248	0.95
0.1852	1.4738	1350	0.1840	0.96
0.1852	1.5284	1400	0.2366	0.95
0.1852	1.5830	1450	0.2322	0.95
0.1137	1.6376	1500	0.1797	0.96
0.1137	1.6921	1550	0.1662	0.96
0.1137	1.7467	1600	0.1762	0.96
0.1137	1.8013	1650	0.1508	0.96
0.1137	1.8559	1700	0.1996	0.95
0.1137	1.9105	1750	0.2072	0.94

Framework versions

Transformers 4.42.2
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1

Task: Text Classification
Library: transformers
Type: bert
Created: Jul 11, 2024
Updated: Jul 11, 2024