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test-finetuned-imdb – AI Model by andywedlake | AlphaNeural AI
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andywedlake
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test-finetuned-imdb
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transformers
tf
distilbert
fill-mask
generated_from_keras_callback
distilbert/distilbert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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andywedlake/test-finetuned-imdb
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: 2.5885
Validation Loss: 2.7934
Epoch: 9
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': {'module': 'transformers.optimization_tf', 'class_name': 'WarmUp', 'config': {'initial_learning_rate': 0.0005, 'decay_schedule_fn': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0005, 'decay_steps': 100, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'warmup_steps': 100, 'power': 1.0, 'name': None}, 'registered_name': 'WarmUp'}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.0001}
training_precision: float32
Training results
Train Loss
Validation Loss
Epoch
4.6321
4.5289
0
4.3391
4.1727
1
4.4752
4.8518
2
4.4115
2.9955
3
3.7038
4.0675
4
3.7644
2.6604
5
3.2356
2.7260
6
3.1930
2.2103
7
3.0317
2.1028
8
2.5885
2.7934
9
Framework versions
Transformers 4.41.2
TensorFlow 2.15.0
Datasets 2.20.0
Tokenizers 0.19.1
