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multi-class-classification-not-evaluated – AI Model by autoevaluate | AlphaNeural AI
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multi-class-classification-not-evaluated
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transformers
pytorch
tensorboard
distilbert
text-classification
generated_from_trainer
emotion
apache-2.0
autotrain_compatible
endpoints_compatible
us
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multi-class-classification
This model is a fine-tuned version of
distilbert-base-uncased
on the emotion dataset. It achieves the following results on the evaluation set:
Loss: 0.2009
Accuracy: 0.928
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: 1
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.2643
1.0
1000
0.2009
0.928
Framework versions
Transformers 4.19.2
Pytorch 1.11.0+cu113
Datasets 2.2.2
Tokenizers 0.12.1
