B001_cleaned – AI Model by Theoreticallyhugo | AlphaNeural AI | AlphaNeural AI

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Theoreticallyhugo/
B001_cleaned

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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B001_cleaned

This model is a fine-tuned version of distilbert-base-uncased on the essay_dataset dataset. It achieves the following results on the evaluation set:

Loss: 2.2117
Accuracy: {'accuracy': 0.10526315789473684}
Precision: {'precision': 0.013157894736842105}
Recall: {'recall': 0.125}
F1: {'f1': 0.02380952380952381}

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
No log	1.0	13	2.2061	{'accuracy': 0.10526315789473684}	{'precision': 0.013157894736842105}	{'recall': 0.125}	{'f1': 0.02380952380952381}
No log	2.0	26	2.2050	{'accuracy': 0.10526315789473684}	{'precision': 0.013157894736842105}	{'recall': 0.125}	{'f1': 0.02380952380952381}
No log	3.0	39	2.2045	{'accuracy': 0.10526315789473684}	{'precision': 0.013157894736842105}	{'recall': 0.125}	{'f1': 0.02380952380952381}
No log	4.0	52	2.2117	{'accuracy': 0.10526315789473684}	{'precision': 0.013157894736842105}	{'recall': 0.125}	{'f1': 0.02380952380952381}

Framework versions

Transformers 4.37.1
Pytorch 2.1.2+cu121
Datasets 2.16.1
Tokenizers 0.15.1