estudiante_S3D_profesor_MViT_kl_RLVS

DanJoshua/estudiante_S3D_profesor_MViT_kl_RLVS

estudiante_S3D_profesor_MViT_kl_RLVS 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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At a glance

Library: transformers
Access: Public
Created: Nov 4, 2024
Updated: Nov 4, 2024
SHA: 1fe5d402

Model card

From the Hugging Face model README

estudiante_S3D_profesor_MViT_kl_RLVS

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

Loss: 0.0504
Accuracy: 0.9868
F1: 0.9868
Precision: 0.9869
Recall: 0.9868
Roc Auc: 0.9987

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: 40
eval_batch_size: 40
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: 320
training_steps: 3200
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall	Roc Auc
0.6173	3.0125	160	0.2047	0.9171	0.9167	0.9261	0.9171	0.9840
0.2463	7.0125	320	0.0819	0.9679	0.9679	0.9688	0.9679	0.9949
0.1257	11.0125	480	0.0515	0.9786	0.9786	0.9786	0.9786	0.9981
0.1012	15.0125	640	0.0533	0.9840	0.9840	0.9840	0.9840	0.9983
0.0633	19.0125	800	0.0562	0.9893	0.9893	0.9893	0.9893	0.9986
0.0721	23.0125	960	0.0503	0.9866	0.9866	0.9866	0.9866	0.9981
0.0721	27.0125	1120	0.0482	0.9759	0.9759	0.9759	0.9759	0.9984
0.056	31.0125	1280	0.0599	0.9866	0.9866	0.9866	0.9866	0.9986
0.0565	35.0125	1440	0.0515	0.9866	0.9866	0.9866	0.9866	0.9985
0.0613	39.0125	1600	0.0436	0.9840	0.9840	0.9840	0.9840	0.9979

Framework versions

Transformers 4.46.1
Pytorch 2.0.1+cu118
Datasets 3.1.0
Tokenizers 0.20.1

Library: transformers
Created: Nov 4, 2024
Updated: Nov 4, 2024