estudiante_MC318_RLVS

DanJoshua/estudiante_MC318_RLVS

estudiante_MC318_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 28, 2024
Updated: Nov 28, 2024
SHA: d96f706a

Model card

From the Hugging Face model README

estudiante_MC318_RLVS

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

Loss: 0.0561
Accuracy: 0.9829
F1: 0.9829
Precision: 0.9829
Recall: 0.9829
Roc Auc: 0.9981

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: 30
eval_batch_size: 30
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: 159
training_steps: 1590
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall	Roc Auc
0.4767	1.0145	79	0.4016	0.9011	0.9010	0.9031	0.9011	0.9736
0.3026	2.0289	158	0.2415	0.9465	0.9465	0.9466	0.9465	0.9904
0.2062	4.0082	237	0.1622	0.9626	0.9626	0.9628	0.9626	0.9935
0.1697	5.0226	316	0.1178	0.9679	0.9679	0.9679	0.9679	0.9950
0.1242	7.0019	395	0.1212	0.9759	0.9759	0.9759	0.9759	0.9962
0.0999	8.0164	474	0.0796	0.9706	0.9706	0.9709	0.9706	0.9963
0.0743	9.0308	553	0.0967	0.9759	0.9759	0.9761	0.9759	0.9975
0.0659	11.0101	632	0.0661	0.9840	0.9840	0.9842	0.9840	0.9975
0.0678	12.0245	711	0.0590	0.9840	0.9840	0.9840	0.9840	0.9987
0.0498	14.0038	790	0.0513	0.9840	0.9840	0.9840	0.9840	0.9982
0.0429	15.0182	869	0.0752	0.9813	0.9813	0.9814	0.9813	0.9983

Framework versions

Transformers 4.46.3
Pytorch 2.0.1+cu118
Datasets 3.1.0
Tokenizers 0.20.3

Library: transformers
Created: Nov 28, 2024
Updated: Nov 28, 2024