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baseline_BERT_10K_steps

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: 0.0356
  • Accuracy: 0.9906
  • Precision: 0.7827
  • Recall: 0.0517
  • F1: 0.0970
  • Hamming: 0.0094

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: 6
  • eval_batch_size: 6
  • 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: 10000

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1 Hamming
No log 0.0 500 0.1602 0.9902 0.0 0.0 0.0 0.0098
No log 0.0 1000 0.0573 0.9902 0.0 0.0 0.0 0.0098
No log 0.0 1500 0.0504 0.9902 0.0 0.0 0.0 0.0098
No log 0.01 2000 0.0492 0.9902 0.0 0.0 0.0 0.0098
No log 0.01 2500 0.0488 0.9902 0.0 0.0 0.0 0.0098
No log 0.01 3000 0.0485 0.9902 0.0 0.0 0.0 0.0098
No log 0.01 3500 0.0477 0.9902 0.0 0.0 0.0 0.0098
No log 0.01 4000 0.0467 0.9902 0.0 0.0 0.0 0.0098
No log 0.01 4500 0.0455 0.9902 0.0 0.0 0.0 0.0098
No log 0.01 5000 0.0442 0.9902 0.0 0.0 0.0 0.0098
No log 0.02 5500 0.0422 0.9902 0.0 0.0 0.0 0.0098
No log 0.02 6000 0.0408 0.9902 0.0 0.0 0.0 0.0098
No log 0.02 6500 0.0394 0.9902 0.0 0.0 0.0 0.0098
No log 0.02 7000 0.0385 0.9902 1.0 0.0011 0.0022 0.0098
No log 0.02 7500 0.0376 0.9903 0.7949 0.0057 0.0113 0.0097
No log 0.02 8000 0.0368 0.9903 0.8071 0.0146 0.0287 0.0097
No log 0.03 8500 0.0363 0.9905 0.7372 0.0465 0.0874 0.0095
No log 0.03 9000 0.0359 0.9905 0.7811 0.0381 0.0727 0.0095
No log 0.03 9500 0.0357 0.9906 0.8029 0.0562 0.1051 0.0094
0.0665 0.03 10000 0.0356 0.9906 0.7827 0.0517 0.0970 0.0094

Framework versions

  • Transformers 4.37.2
  • Pytorch 1.12.1+cu113
  • Datasets 2.16.1
  • Tokenizers 0.15.1
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Safetensors
Model size
110M params
Tensor type
F32
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Finetuned from

Dataset used to train jordyvl/baseline_BERT_10K_steps

Evaluation results