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jmLuis/
Electra-Thesis-NonKFold

Name: Electra-Thesis-NonKFold
Availability: InStock

generated_from_trainer

apache-2.0

autotrain_compatible

endpoints_compatible

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Electra-Thesis-NonKFold

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

Loss: 1.4914
F1: 0.6390
Recall: 0.6390
Accuracy: 0.6390

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: 2e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Recall	Accuracy
1.6531	1.0	1446	1.3688	0.5851	0.5851	0.5851
1.2404	2.0	2892	1.2674	0.6230	0.6230	0.6230
1.0544	3.0	4338	1.2389	0.6322	0.6322	0.6322
0.9189	4.0	5784	1.2293	0.6376	0.6376	0.6376
0.8034	5.0	7230	1.3130	0.6384	0.6384	0.6384
0.7351	6.0	8676	1.3463	0.6390	0.6390	0.6390
0.6481	7.0	10122	1.3858	0.6385	0.6385	0.6385
0.5885	8.0	11568	1.4379	0.6372	0.6372	0.6372
0.5533	9.0	13014	1.4792	0.6344	0.6344	0.6344
0.5285	10.0	14460	1.4914	0.6390	0.6390	0.6390

Framework versions

Transformers 4.28.0
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3

jmLuis/Electra-Thesis-NonKFold

Electra-Thesis-NonKFold

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jmLuis/
Electra-Thesis-NonKFold