Beta
Explore
Marketplace
Neural Labs
Playground
Wallet
Docs
emotion-analysis-with-distilbert – AI Model by denizkaya2022 | AlphaNeural AI
You can deploy this model and start earning money today!
denizkaya2022
/
emotion-analysis-with-distilbert
like
0
transformers
tf
distilbert
text-classification
generated_from_keras_callback
distilbert/distilbert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
Views
No views yet
Model card
Files and Versions
Community
API
Deploy
denizkaya2022/emotion-analysis-with-distilbert
This model is a fine-tuned version of
distilbert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 0.1308
Validation Loss: 0.1430
Train Accuracy: 0.93
Epoch: 1
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:
optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': 5e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
training_precision: float32
Training results
Train Loss
Validation Loss
Train Accuracy
Epoch
0.3786
0.1376
0.932
0
0.1308
0.1430
0.93
1
Framework versions
Transformers 4.35.2
TensorFlow 2.15.0
Datasets 2.15.0
Tokenizers 0.15.0
