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distilbert-base-uncased-finetuned-emotion – AI Model by takizawa | AlphaNeural AI
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takizawa
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distilbert-base-uncased-finetuned-emotion
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transformers
pytorch
tensorboard
distilbert
text-classification
generated_from_trainer
emotion
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: 0.2251
Accuracy: 0.925
F1: 0.9250
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
0.8481
1.0
250
0.3248
0.907
0.9028
0.2595
2.0
500
0.2251
0.925
0.9250
Framework versions
Transformers 4.13.0
Pytorch 1.12.1+cu113
Datasets 1.16.1
Tokenizers 0.10.3
