bert-tweets-covid – AI Model by jariasf | AlphaNeural AI

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jariasf/
bert-tweets-covid

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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bert-tweets-covid

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: 0.2976
Accuracy: 0.9252
F1-score: 0.9258
Precision: 0.9272
Recall: 0.9252

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: 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: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1-score	Precision	Recall
0.5002	1.0	513	0.3214	0.8942	0.8943	0.9006	0.8942
0.2524	2.0	1026	0.2472	0.9220	0.9219	0.9225	0.9220
0.1686	3.0	1539	0.2503	0.9277	0.9275	0.9277	0.9277
0.1171	4.0	2052	0.2626	0.9325	0.9324	0.9324	0.9325
0.0758	5.0	2565	0.2976	0.9252	0.9258	0.9272	0.9252

Framework versions

Transformers 4.28.0
Pytorch 2.0.0+cu118
Datasets 2.11.0
Tokenizers 0.13.3