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bert-emotion – AI Model by gabella | AlphaNeural AI
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gabella
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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: 1.1951
Precision: 0.7350
Recall: 0.7334
Fscore: 0.7341
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
0.8468
1.0
815
0.7465
0.7116
0.6096
0.6325
0.5105
2.0
1630
0.9035
0.7532
0.7111
0.7276
0.2492
3.0
2445
1.1951
0.7350
0.7334
0.7341
Framework versions
Transformers 4.25.1
Pytorch 1.13.0+cu116
Datasets 2.8.0
Tokenizers 0.13.2
