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: 0.2645
Accuracy: 0.92
F1: 0.9197

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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.693	0.3333	2	0.6873	0.9444	0.9443
0.6837	0.6667	4	0.6665	0.8827	0.8811
0.6549	1.0	6	0.6281	0.9012	0.9003
0.6176	1.3333	8	0.5559	0.9259	0.9255
0.5435	1.6667	10	0.4569	0.9568	0.9568
0.4427	2.0	12	0.3831	0.9630	0.9629
0.378	2.3333	14	0.3179	0.9691	0.9691
0.3193	2.6667	16	0.2640	0.9753	0.9753
0.2508	3.0	18	0.2314	0.9815	0.9815
0.2473	3.3333	20	0.2128	0.9815	0.9815
0.2253	3.6667	22	0.1980	0.9815	0.9815
0.1778	4.0	24	0.1823	0.9815	0.9815
0.1924	4.3333	26	0.1721	0.9815	0.9815
0.1731	4.6667	28	0.1634	0.9877	0.9877
0.1527	5.0	30	0.1580	0.9877	0.9877
0.1466	5.3333	32	0.1544	0.9877	0.9877
0.1809	5.6667	34	0.1517	0.9877	0.9877
0.1339	6.0	36	0.1509	0.9877	0.9877

Framework versions

Transformers 4.47.1
Pytorch 2.5.1+cu124
Datasets 3.2.0
Tokenizers 0.21.0

livinNector/m-minilm-l12-h384-dra-tam-ai-gen-review-classification-finetune

m-minilm-l12-h384-dra-tam-ai-gen-review-classification-finetune

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

livinNector/
m-minilm-l12-h384-dra-tam-ai-gen-review-classification-finetune