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finetune_sst2 – AI Model by dewanshsinghchandel | AlphaNeural AI
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dewanshsinghchandel
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finetune_sst2
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transformers
tf
bert
text-classification
generated_from_keras_callback
dewanshsinghchandel/Bert-Base-Uncased-Pretrained
finetune
autotrain_compatible
endpoints_compatible
us
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dewanshsinghchandel/finetune_sst2
This model is a fine-tuned version of
dewanshsinghchandel/Bert-Base-Uncased-Pretrained
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: nan
Train Sparse Categorical Accuracy: 0.4220
Validation Loss: nan
Validation Sparse Categorical Accuracy: 0.3760
Epoch: 2
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
Train Sparse Categorical Accuracy
Validation Loss
Validation Sparse Categorical Accuracy
Epoch
nan
0.4160
nan
0.3760
0
nan
0.4220
nan
0.3760
1
nan
0.4220
nan
0.3760
2
Framework versions
Transformers 4.35.2
TensorFlow 2.14.0
Datasets 2.15.0
Tokenizers 0.15.0
