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clasificador-rotten-tomatoes-bert-base-uncased – AI Model by nlmaldonadog | AlphaNeural AI
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nlmaldonadog
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clasificador-rotten-tomatoes-bert-base-uncased
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transformers
tensorboard
safetensors
bert
text-classification
classification
generated_from_trainer
google-bert/bert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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clasificador-rotten-tomatoes-bert-base-uncased
This model is a fine-tuned version of
bert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.7643
Accuracy: 0.8659
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:
learning_rate: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3.0
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.3987
1.0
1067
0.3859
0.8471
0.2365
2.0
2134
0.6696
0.8612
0.0844
3.0
3201
0.7643
0.8659
Framework versions
Transformers 4.40.2
Pytorch 2.2.1+cu121
Datasets 2.19.1
Tokenizers 0.19.1
