bert-base-uncased-finetuned-emotion – AI Model by nikitakapitan | AlphaNeural AI

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nikitakapitan/
bert-base-uncased-finetuned-emotion

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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-emotion

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

Loss: 0.1651
Accuracy: {'accuracy': 0.9355}
F1: {'f1': 0.935388774713548}

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: 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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.2519	1.0	1000	0.1878	{'accuracy': 0.9325}	{'f1': 0.9323540471733189}
0.1434	2.0	2000	0.1799	{'accuracy': 0.9335}	{'f1': 0.9341179573678701}
0.0907	3.0	3000	0.1651	{'accuracy': 0.9355}	{'f1': 0.935388774713548}

Framework versions

Transformers 4.33.1
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3