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test-codes – AI Model by pinark | AlphaNeural AI

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test-codes

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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test-codes

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.1138
Accuracy: 0.9722
F1: 0.9706

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

Framework versions

Transformers 4.28.0
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3