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test_implementation

This model is a fine-tuned version of bert-base-uncased on the arxiv_dataset dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6736
  • Accuracy: 0.5926
  • Precision: 0.0090
  • Recall: 0.3751
  • F1: 0.0177
  • Hamming: 0.4074

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: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • training_steps: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1 Hamming
0.7077 0.0 5 0.6857 0.5529 0.0089 0.4040 0.0173 0.4471
0.6801 0.0 10 0.6736 0.5926 0.0090 0.3751 0.0177 0.4074

Framework versions

  • Transformers 4.37.2
  • Pytorch 1.12.1+cu113
  • Datasets 2.16.1
  • Tokenizers 0.15.1
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F32
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Finetuned from

Dataset used to train jordyvl/test_implementation

Evaluation results