bert-base-uncased-english-sentweet-profane – AI Model by jayanta | AlphaNeural AI

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jayanta/
bert-base-uncased-english-sentweet-profane

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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bert-base-uncased-english-sentweet-profane

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

Loss: 0.9193
Accuracy: 0.7951
Precision: 0.8047
Recall: 0.8042
F1: 0.7951

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: 5e-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: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
No log	1.0	81	0.4563	0.8160	0.8317	0.8275	0.8159
No log	2.0	162	0.4613	0.8125	0.8271	0.8236	0.8124
No log	3.0	243	0.5956	0.7882	0.8012	0.7987	0.7881
No log	4.0	324	0.7474	0.7847	0.7950	0.7941	0.7847
No log	5.0	405	0.8416	0.8021	0.8029	0.8061	0.8017
No log	6.0	486	0.9193	0.7951	0.8047	0.8042	0.7951

Framework versions

Transformers 4.24.0
Pytorch 1.13.1+cu117
Datasets 2.6.1
Tokenizers 0.11.0