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livinNector/
m-minilm-l12-h384-dra-tam-mal-aw-classification-loreft

Name: m-minilm-l12-h384-dra-tam-mal-aw-classification-loreft
Availability: InStock

transformers

generated_from_trainer

microsoft/Multilingual-MiniLM-L12-H384

finetune

mit

endpoints_compatible

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

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: 0.6937
Accuracy: 0.4735
F1: 0.6427

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
0.6923	0.4444	20	0.6920	0.5265	0.0
0.6929	0.8889	40	0.6931	0.5167	0.6413
0.6949	1.3333	60	0.6934	0.4735	0.6427
0.6927	1.7778	80	0.6941	0.4735	0.6427
0.693	2.2222	100	0.6944	0.4735	0.6427
0.693	2.6667	120	0.6939	0.4735	0.6427
0.693	3.1111	140	0.6939	0.4735	0.6427
0.6929	3.5556	160	0.6933	0.4735	0.6427
0.693	4.0	180	0.6937	0.4735	0.6427
0.6928	4.4444	200	0.6936	0.4735	0.6427
0.693	4.8889	220	0.6940	0.4735	0.6427
0.6933	5.3333	240	0.6937	0.4735	0.6427
0.6928	5.7778	260	0.6937	0.4735	0.6427

Framework versions

Transformers 4.45.2
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.20.3

livinNector/m-minilm-l12-h384-dra-tam-mal-aw-classification-loreft

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

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

livinNector/
m-minilm-l12-h384-dra-tam-mal-aw-classification-loreft