imdb-bert-large / README.md
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metadata
license: apache-2.0
base_model: bert-large-uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: bert-large
    results: []

bert-large

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

  • Loss: 0.9621
  • Accuracy: 0.8887

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: 5e-05
  • train_batch_size: 32
  • eval_batch_size: 256
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 782 0.2848 0.8852
0.3133 2.0 1564 0.3038 0.8888
0.1751 3.0 2346 0.5035 0.8791
0.1057 4.0 3128 0.5942 0.885
0.1057 5.0 3910 0.5220 0.8764
0.0733 6.0 4692 0.6981 0.8823
0.0439 7.0 5474 0.6775 0.8833
0.0371 8.0 6256 0.6118 0.8891
0.0277 9.0 7038 0.7128 0.8864
0.0277 10.0 7820 0.7555 0.8868
0.0202 11.0 8602 0.7618 0.8888
0.0141 12.0 9384 0.7654 0.8842
0.0125 13.0 10166 0.8345 0.8867
0.0125 14.0 10948 0.8073 0.8844
0.0077 15.0 11730 0.7047 0.8887
0.0071 16.0 12512 0.8622 0.8891
0.004 17.0 13294 0.8655 0.8900
0.0031 18.0 14076 0.9096 0.8898
0.0031 19.0 14858 0.9454 0.8892
0.0016 20.0 15640 0.9621 0.8887

Framework versions

  • Transformers 4.37.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.0
  • Tokenizers 0.15.2