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finetuned-bert-base-uncased-on-HOPE

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metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: finetuned-bert-base-uncased-on-HOPE
    results: []

finetuned-bert-base-uncased-on-HOPE

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

  • Loss: 1.3515
  • Accuracy: 0.5345

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: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.7368 1.0 289 1.6685 0.4526
1.3051 2.0 578 1.4303 0.5176
1.0563 3.0 867 1.3849 0.5438
1.1101 4.0 1156 1.4233 0.5185
0.9118 5.0 1445 1.5438 0.5023
0.7889 6.0 1734 1.6832 0.5014
0.4892 7.0 2023 1.8469 0.4824
0.3739 8.0 2312 2.0680 0.4734
0.3813 9.0 2601 2.1392 0.4706
0.3459 10.0 2890 2.2772 0.4761
0.2323 11.0 3179 2.3445 0.4688
0.1977 12.0 3468 2.4754 0.4761
0.2351 13.0 3757 2.5912 0.4661
0.1991 14.0 4046 2.6713 0.4743
0.2239 15.0 4335 2.7262 0.4706
0.155 16.0 4624 2.7958 0.4697
0.1675 17.0 4913 2.8367 0.4724
0.1471 18.0 5202 2.8619 0.4715
0.1973 19.0 5491 2.8744 0.4770
0.1902 20.0 5780 2.8865 0.4752

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1