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bert-emotion – AI Model by jsilver | AlphaNeural AI
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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: 1.1413
Precision: 0.7506
Recall: 0.7243
Fscore: 0.7340
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
0.8556
1.0
815
0.7854
0.7461
0.5929
0.6088
0.5369
2.0
1630
0.9014
0.7549
0.7278
0.7359
0.2571
3.0
2445
1.1413
0.7506
0.7243
0.7340
Framework versions
Transformers 4.29.2
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3
