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bert-emotion – AI Model by prasak1 | AlphaNeural AI
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prasak1
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bert-emotion
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transformers
pytorch
tensorboard
distilbert
text-classification
generated_from_trainer
tweet_eval
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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bert-emotion
This model is a fine-tuned version of
distilbert-base-cased
on the tweet_eval dataset. It achieves the following results on the evaluation set:
Loss: 1.2637
Precision: 0.6952
Recall: 0.7038
Fscore: 0.6978
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: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
Fscore
0.857
1.0
815
0.7067
0.7321
0.6642
0.6881
0.5227
2.0
1630
0.9861
0.7329
0.6725
0.6916
0.2652
3.0
2445
1.2637
0.6952
0.7038
0.6978
Framework versions
Transformers 4.25.1
Pytorch 1.13.0+cu116
Datasets 2.8.0
Tokenizers 0.13.2
