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1023 – AI Model by tingchih | AlphaNeural AI
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tingchih
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1023
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transformers
pytorch
tensorboard
distilbert
text-classification
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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Model card
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1023
This model is a fine-tuned version of
distilbert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Accuracy: 28.96%
single_doc_single_modal Recall: 50.21%
single_doc_single_modal Precision: 26.16%
single_doc_multi_modals Recall: 25.16%
single_doc_multi_modals Precision: 45.62%
multi_docs_single_modal Recall: 17.31%
single_doc_multi_modals Precision: 40.59%
multi_docs_multi_modals Recall: 0%
multi_docs_multi_modals Precision: 0%
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: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
Framework versions
Transformers 4.28.1
Pytorch 1.13.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3
