profesor_MViT_O_VIOPERU

DanJoshua/profesor_MViT_O_VIOPERU

profesor_MViT_O_VIOPERU 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 3, 2024
Updated: Nov 3, 2024
SHA: 47fdf89e

Model card

From the Hugging Face model README

profesor_MViT_O_VIOPERU

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

Loss: 0.5344
Accuracy: 0.8661
F1: 0.8660
Precision: 0.8671
Recall: 0.8661
Roc Auc: 0.9058

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: 22
eval_batch_size: 22
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: 90
training_steps: 900
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall	Roc Auc
0.6682	7.0067	90	0.6678	0.6111	0.5504	0.7849	0.6111	0.8791
0.5925	14.0133	180	0.6043	0.8519	0.8519	0.8519	0.8519	0.875
0.4774	22.0067	270	0.5004	0.8889	0.8886	0.8907	0.8889	0.8929
0.3457	29.0133	360	0.4336	0.8704	0.8702	0.8707	0.8704	0.8929
0.221	37.0067	450	0.3516	0.8519	0.8519	0.8519	0.8519	0.8984
0.139	44.0133	540	0.3847	0.8704	0.8697	0.8745	0.8704	0.9080
0.0955	52.0067	630	0.3967	0.8704	0.8675	0.8963	0.8704	0.9121
0.0773	59.0133	720	0.4283	0.8704	0.8697	0.8745	0.8704	0.9032
0.0584	67.0067	810	0.3643	0.8889	0.8880	0.8971	0.8889	0.9114
0.0441	74.0133	900	0.4218	0.8519	0.8519	0.8519	0.8519	0.9100

Framework versions

Transformers 4.46.1
Pytorch 2.0.1+cu118
Datasets 3.1.0
Tokenizers 0.20.1

Library: transformers
Created: Nov 3, 2024
Updated: Nov 3, 2024