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FNet_Classification – AI Model by Shruthikaa | AlphaNeural AI | AlphaNeural AI
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Shruthikaa
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FNet_Classification
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transformers
pytorch
fnet
text-classification
generated_from_trainer
google/fnet-base
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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FNet_Classification
This model is a fine-tuned version of
google/fnet-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.3889
Accuracy: 0.813
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: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.5529
1.0
625
0.4144
0.804
0.4314
2.0
1250
0.3889
0.813
Framework versions
Transformers 4.32.1
Pytorch 2.2.1+cpu
Datasets 2.12.0
Tokenizers 0.13.2
