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distilbert-base-uncased-finetuned-imdb – AI Model by syy88824 | AlphaNeural AI
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syy88824
/
distilbert-base-uncased-finetuned-imdb
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0
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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syy88824/distilbert-base-uncased-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: 2.3163
Validation Loss: 2.3017
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': {'module': 'transformers.optimization_tf', 'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': -875, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'warmup_steps': 1500, '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': 0.01}
training_precision: mixed_float16
Training results
Train Loss
Validation Loss
Epoch
2.3995
2.2657
0
2.3558
2.2605
1
2.3314
2.2569
2
2.3124
2.2709
3
2.3163
2.3017
4
Framework versions
Transformers 4.47.1
TensorFlow 2.17.1
Datasets 3.2.0
Tokenizers 0.21.0
