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sentiment-model – AI Model by Camille03 | AlphaNeural AI
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Camille03
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sentiment-model
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transformers
pytorch
bert
text-classification
generated_from_trainer
mit
autotrain_compatible
endpoints_compatible
us
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sentiment-model
This model is a fine-tuned version of
prajjwal1/bert-tiny
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.5607
Accuracy: 0.7833
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
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.5278
1.0
1500
0.4808
0.7817
0.3811
2.0
3000
0.5271
0.78
0.3366
3.0
4500
0.5607
0.7833
Framework versions
Transformers 4.18.0
Pytorch 1.12.1+cu102
Datasets 2.12.0
Tokenizers 0.12.1
