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UniqueProcessedText – AI Model by Kamer | AlphaNeural AI

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Kamer/
UniqueProcessedText

like

0

text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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UniqueProcessedText

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

eval_loss: 0.5682
eval_Accuracy: 0.8841
eval_F1_macro: 0.7994
eval_F1_class_0: 0.8918
eval_F1_class_1: 0.5714
eval_F1_class_2: 0.9309
eval_F1_class_3: 0.8571
eval_F1_class_4: 0.8571
eval_F1_class_5: 0.8667
eval_F1_class_6: 0.7647
eval_F1_class_7: 0.9545
eval_F1_class_8: 0.9831
eval_F1_class_9: 0.7692
eval_F1_class_10: 0.8533
eval_F1_class_11: 0.7143
eval_F1_class_12: 0.8199
eval_F1_class_13: 0.8889
eval_F1_class_14: 0.8608
eval_F1_class_15: 0.6486
eval_F1_class_16: 0.0
eval_F1_class_17: 0.9848
eval_F1_class_18: 0.8485
eval_F1_class_19: 0.9231
eval_runtime: 17.459
eval_samples_per_second: 64.723
eval_steps_per_second: 4.067
epoch: 0.92
step: 3000

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: 3

Framework versions

Transformers 4.32.0
Pytorch 2.0.1+cu117
Datasets 2.14.4
Tokenizers 0.13.3