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finetuning-sentiment-analysis-bert – AI Model by aruca | AlphaNeural AI
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aruca
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finetuning-sentiment-analysis-bert
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transformers
tensorboard
safetensors
bert
text-classification
generated_from_trainer
google-bert/bert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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finetuning-sentiment-analysis-bert
This model is a fine-tuned version of
bert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.2020
Accuracy: 0.7900
F1: [0.7917078 0.75420168 0.83531565]
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: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 6
Training results
Framework versions
Transformers 4.36.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.0
