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bert-base-uncased-emotion – AI Model by RicoCHEH | AlphaNeural AI
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RicoCHEH
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bert-base-uncased-emotion
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transformers
safetensors
bert
text-classification
generated_from_trainer
emotion
google-bert/bert-base-uncased
finetune
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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bert-base-uncased-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: 0.1303
Accuracy: 0.9385
F1: 0.9391
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: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
0.5346
1.0
250
0.1825
0.931
0.9315
0.1336
2.0
500
0.1303
0.9385
0.9391
Framework versions
Transformers 4.35.0
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1
