estudiante_Swin3D_RWF2000

DanJoshua/estudiante_Swin3D_RWF2000

estudiante_Swin3D_RWF2000 is a machine learning model from DanJoshua. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.

should probably proofread and complete it, then remove this comment. --

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Model card

From the Hugging Face model README

estudiante_Swin3D_RWF2000

This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.4354
Accuracy: 0.8975
F1: 0.8974
Precision: 0.8997
Recall: 0.8975
Roc Auc: 0.9593

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: 1e-05
train_batch_size: 15
eval_batch_size: 15
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 318
training_steps: 3180
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall	Roc Auc
0.4565	1.0160	159	0.3441	0.8625	0.8624	0.8640	0.8625	0.9311
0.2952	2.0321	318	0.3023	0.8675	0.8675	0.8677	0.8675	0.9492
0.2393	4.0142	477	0.3530	0.88	0.8798	0.8831	0.88	0.9555
0.2012	5.0302	636	0.3451	0.89	0.8900	0.8906	0.89	0.9576
0.1724	7.0123	795	0.3739	0.8725	0.8719	0.8794	0.8725	0.9617
0.1847	8.0283	954	0.3768	0.88	0.8798	0.8831	0.88	0.9607
0.1522	10.0104	1113	0.3928	0.89	0.8898	0.8925	0.89	0.9671
0.152	11.0264	1272	0.4155	0.9025	0.9025	0.9028	0.9025	0.9636
0.1664	13.0085	1431	0.4156	0.8875	0.8874	0.8883	0.8875	0.9651
0.1302	14.0245	1590	0.4375	0.895	0.8949	0.8960	0.895	0.9656
0.1093	16.0066	1749	0.4739	0.9	0.8999	0.9014	0.9	0.9657
0.1204	17.0226	1908	0.5818	0.8875	0.8869	0.8958	0.8875	0.9654
0.1252	19.0047	2067	0.4423	0.9	0.9000	0.9004	0.9	0.9694

Framework versions

Transformers 4.46.1
Pytorch 2.0.1+cu118
Datasets 3.1.0
Tokenizers 0.20.2

Library: transformers
Created: Nov 5, 2024
Updated: Nov 6, 2024