sequence-ranker-dbpedia-last-layer

This model is a fine-tuned version of bert-large-cased on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7623
  • F1: 0.0
  • Precision: 0.0
  • Recall: 0.0
  • Accuracy: 0.8266

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: 1e-05
  • train_batch_size: 2
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 2

Training results

Training Loss Epoch Step Validation Loss F1 Precision Recall Accuracy
0.5959 1.0 284 0.7652 0.0 0.0 0.0 0.8266
0.5869 2.0 568 0.7623 0.0 0.0 0.0 0.8266

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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