bert-base-goemotions – AI Model by IsaacZhy | AlphaNeural AI

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IsaacZhy/
bert-base-goemotions

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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bert-base-goemotions

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

Loss: 0.1539
F1: 0.5727
Roc Auc: 0.7796
Accuracy: 0.4375

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: 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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.0833	1.0	2714	0.0876	0.5453	0.7189	0.4243
0.0719	2.0	5428	0.0867	0.5586	0.7322	0.4399
0.0575	3.0	8142	0.0943	0.5736	0.7523	0.4665
0.0411	4.0	10856	0.1064	0.5655	0.7580	0.4574
0.0301	5.0	13570	0.1167	0.5622	0.7591	0.4517
0.0217	6.0	16284	0.1279	0.5579	0.7648	0.4375
0.015	7.0	18998	0.1367	0.5663	0.7759	0.4333
0.0102	8.0	21712	0.1445	0.5695	0.7793	0.4322
0.0077	9.0	24426	0.1491	0.5725	0.7795	0.4366
0.0057	10.0	27140	0.1539	0.5727	0.7796	0.4375

Framework versions

Transformers 4.26.0
Pytorch 1.13.1+cu116
Datasets 2.9.0
Tokenizers 0.13.2