m-minilm-l12-h384-dra-tam-mal-aw-classification-finetune

This model is a fine-tuned version of microsoft/Multilingual-MiniLM-L12-H384 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.5902
• Accuracy: 0.7441
• F1: 0.7577

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: 0.0001
• train_batch_size: 128
• eval_batch_size: 128
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.6813	0.4444	20	0.6168	0.6903	0.7027
0.6418	0.8889	40	0.5810	0.7058	0.7058
0.5704	1.3333	60	0.5545	0.7205	0.6946
0.5575	1.7778	80	0.5344	0.7359	0.7457
0.5107	2.2222	100	0.5341	0.7498	0.7256
0.4649	2.6667	120	0.5298	0.7506	0.7528
0.4559	3.1111	140	0.5420	0.7522	0.7185
0.4031	3.5556	160	0.5952	0.7253	0.7524
0.3834	4.0	180	0.5535	0.7596	0.7476
0.3359	4.4444	200	0.5902	0.7441	0.7577
0.3423	4.8889	220	0.5629	0.7563	0.7498
0.2728	5.3333	240	0.5906	0.7588	0.7513
0.289	5.7778	260	0.6064	0.7555	0.7496

Framework versions

• Transformers 4.45.2
• Pytorch 2.5.1+cu121
• Datasets 3.2.0
• Tokenizers 0.20.3