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