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distilbert-base-uncased-finetuned-emotion – AI Model by MJQing | AlphaNeural AI
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MJQing
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distilbert-base-uncased-finetuned-emotion
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transformers
tensorboard
safetensors
distilbert
text-classification
generated_from_trainer
emotion
distilbert/distilbert-base-uncased
finetune
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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distilbert-base-uncased-finetuned-emotion
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: 0.2037
Accuracy: 0.928
F1: 0.9278
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: 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
0.8259
1.0
250
0.2929
0.9095
0.9083
0.2342
2.0
500
0.2037
0.928
0.9278
Framework versions
Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2
