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historical-events-reimagined – AI Model by Kaludi | AlphaNeural AI
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Kaludi
/
historical-events-reimagined
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transformers
tf
bart
text2text-generation
generated_from_keras_callback
mit
endpoints_compatible
us
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historical-events-reimagined
This model is a fine-tuned version of
philschmid/bart-large-cnn-samsum
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 0.5102
Validation Loss: 2.2624
Epoch: 4
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': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
training_precision: float32
Training results
Train Loss
Validation Loss
Epoch
2.7539
2.1578
0
1.6416
1.9498
1
1.1524
1.9922
2
0.7703
2.1343
3
0.5102
2.2624
4
Framework versions
Transformers 4.27.3
TensorFlow 2.11.0
Datasets 2.10.1
Tokenizers 0.13.2
