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bert-large-uncased-sst-2-16-13-30

Text Classification
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PyTorch
bert
Generated from Trainer
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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-uncased-sst-2-16-13-30
    results: []

bert-large-uncased-sst-2-16-13-30

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: 0.6328
  • Accuracy: 0.625

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: 1.5e-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_steps: 5
  • num_epochs: 30

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 1 0.7326 0.5
No log 2.0 2 0.7299 0.5
No log 3.0 3 0.7258 0.5
No log 4.0 4 0.7173 0.5
No log 5.0 5 0.7098 0.5
No log 6.0 6 0.7019 0.4688
No log 7.0 7 0.6969 0.5
No log 8.0 8 0.6889 0.5312
No log 9.0 9 0.6846 0.5625
0.6763 10.0 10 0.6781 0.5625
0.6763 11.0 11 0.6697 0.5938
0.6763 12.0 12 0.6681 0.625
0.6763 13.0 13 0.6675 0.625
0.6763 14.0 14 0.6668 0.625
0.6763 15.0 15 0.6666 0.625
0.6763 16.0 16 0.6648 0.5938
0.6763 17.0 17 0.6607 0.625
0.6763 18.0 18 0.6589 0.6562
0.6763 19.0 19 0.6564 0.6562
0.4935 20.0 20 0.6533 0.6562
0.4935 21.0 21 0.6502 0.6562
0.4935 22.0 22 0.6472 0.5938
0.4935 23.0 23 0.6445 0.5938
0.4935 24.0 24 0.6418 0.5938
0.4935 25.0 25 0.6391 0.5938
0.4935 26.0 26 0.6370 0.5938
0.4935 27.0 27 0.6353 0.5938
0.4935 28.0 28 0.6341 0.625
0.4935 29.0 29 0.6333 0.625
0.3659 30.0 30 0.6328 0.625

Framework versions

  • Transformers 4.32.0.dev0
  • Pytorch 2.0.1+cu118
  • Datasets 2.4.0
  • Tokenizers 0.13.3