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text_to_topic – AI Model by Sandrro | AlphaNeural AI | AlphaNeural AI
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Sandrro
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text_to_topic
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transformers
pytorch
tensorboard
bert
text-classification
generated_from_trainer
mit
autotrain_compatible
endpoints_compatible
us
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Model card
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text_to_subfunction_v10_2
This model is a fine-tuned version of
cointegrated/rubert-tiny2
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.5115
F1: 0.5638
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: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
F1
1.8616
1.0
5400
1.7457
0.4607
1.4576
2.0
10800
1.5115
0.5638
Framework versions
Transformers 4.27.1
Pytorch 2.1.0.dev20230414+cu117
Datasets 2.9.0
Tokenizers 0.13.3
