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naya-model – AI Model by Gkumi | AlphaNeural AI

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Gkumi/
naya-model

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token-classification

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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Gkumi/naya-model

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

precision: 0.9260
recall: 0.9306
f1: 0.9283
accuracy: 0.9657

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:

num_train_epochs: 5
train_batch_size: 16
eval_batch_size: 32
learning_rate: 2e-05
weight_decay_rate: 0.01
num_warmup_steps: 0
fp16: True

Framework versions

Transformers 4.40.0
Pytorch 2.2.2+cu121
Datasets 2.18.0
Tokenizers 0.19.1