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bert-base-uncased-finetuned-emotion – AI Model by JayWang7 | AlphaNeural AI
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JayWang7
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bert-base-uncased-finetuned-emotion
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transformers
pytorch
tensorboard
bert
text-classification
generated_from_trainer
emotion
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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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: 0.2242
Accuracy: 0.917
F1: 0.9175
Model description
Label-0 = sadness Label-1 = joy Label-2 = love Label-3 = anger Label-4 = fear Label-5 = surprise
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: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
No log
1.0
250
0.3240
0.8945
0.8928
No log
2.0
500
0.2242
0.917
0.9175
Framework versions
Transformers 4.30.0
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.13.3
