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