arabert_baseline_vocabulary_task3_fold0

This model is a fine-tuned version of aubmindlab/bert-base-arabertv02 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.7079
• Qwk: 0.0222
• Mse: 0.6865

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	Qwk	Mse
No log	0.6667	2	4.5600	-0.0382	4.4780
No log	1.3333	4	1.9301	-0.1611	1.8653
No log	2.0	6	1.6014	-0.1987	1.5679
No log	2.6667	8	0.9403	0.0222	0.9126
No log	3.3333	10	0.9340	0.0222	0.9239
No log	4.0	12	1.2406	0.1895	1.2359
No log	4.6667	14	0.7820	0.0222	0.7685
No log	5.3333	16	0.6609	-0.0476	0.6329
No log	6.0	18	0.6633	0.2524	0.6395
No log	6.6667	20	0.8454	0.0	0.8291
No log	7.3333	22	0.9897	0.0	0.9771
No log	8.0	24	0.9105	0.0	0.8961
No log	8.6667	26	0.7687	0.0	0.7499
No log	9.3333	28	0.7158	0.0222	0.6948
No log	10.0	30	0.7079	0.0222	0.6865

Framework versions

• Transformers 4.44.0
• Pytorch 2.4.0
• Datasets 2.21.0
• Tokenizers 0.19.1