Modelpublic

LovenOO/distilBERT_without_preprocessing

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face

0likes5downloads

Model Card

LovenOO/distilBERTwithoutpreprocessing

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

—Train Loss: 0.1466
—Validation Loss: 0.3625
—Train Precision: 0.8491
—Train Recall: 0.8642
—Train F1: 0.8544
—Train Accuracy: 0.8906
—Epoch: 5

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:

—optimizer: {'name': 'Adam', 'learningrate': {'module': 'keras.optimizers.schedules', 'classname': 'PolynomialDecay', 'config': {'initiallearningrate': 2e-05, 'decaysteps': 2565, 'endlearningrate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registeredname': None}, 'decay': 0.0, 'beta1': 0.9, 'beta2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
—training_precision: float32

Training results

Train Loss	Validation Loss	Train Precision	Train Recall	Train F1	Train Accuracy	Epoch
0.8177	0.4723	0.8407	0.7879	0.7948	0.8575	0
0.3642	0.3777	0.8666	0.8315	0.8465	0.8847	1
0.2734	0.3804	0.8466	0.8563	0.8471	0.8872	2
0.2020	0.3704	0.8526	0.8663	0.8551	0.8896	3
0.1638	0.3625	0.8491	0.8642	0.8544	0.8906	4
0.1466	0.3625	0.8491	0.8642	0.8544	0.8906	5

Framework versions

—Transformers 4.24.0
—TensorFlow 2.13.0
—Datasets 2.14.2
—Tokenizers 0.11.0