bert-base-uncased-finetuned-stationary-chatgptDS – AI Model by MKS3099 | AlphaNeural AI

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MKS3099/
bert-base-uncased-finetuned-stationary-chatgptDS

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text-classification

generated_from_trainer

google-bert/bert-base-uncased

autotrain_compatible

endpoints_compatible

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bert-base-uncased-finetuned-stationary-chatgptDS

This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.7019
Accuracy: 0.84
F1: 0.8367

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: 64
eval_batch_size: 64
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	Accuracy	F1
0.5554	1.0	75	0.4860	0.7867	0.7674
0.3768	2.0	150	0.4438	0.8117	0.8103
0.2551	3.0	225	0.4781	0.8333	0.8284
0.1581	4.0	300	0.4850	0.8383	0.8334
0.1051	5.0	375	0.5698	0.845	0.8381
0.0726	6.0	450	0.6293	0.845	0.8439
0.05	7.0	525	0.6414	0.8417	0.8396
0.031	8.0	600	0.7114	0.8483	0.8474
0.026	9.0	675	0.6890	0.8467	0.8433
0.0198	10.0	750	0.7019	0.84	0.8367

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.0