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

bert-base-uncased-swag

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: 1.3863
  • Accuracy: 0.2929

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: 0.0005
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 321
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 63 1.4088 0.2273
No log 2.0 126 1.4448 0.2323
No log 3.0 189 1.6544 0.2323
No log 4.0 252 1.8585 0.2424
No log 5.0 315 1.9976 0.2121
No log 6.0 378 1.8819 0.2071
No log 7.0 441 1.3863 0.1919
0.7104 8.0 504 1.3863 0.2929
0.7104 9.0 567 1.3863 0.1919
0.7104 10.0 630 1.3863 0.0354
0.7104 11.0 693 1.3863 0.1010
0.7104 12.0 756 1.3863 0.1364
0.7104 13.0 819 1.3863 0.0
0.7104 14.0 882 1.3863 0.1111
0.7104 15.0 945 1.3863 0.0556
1.4022 16.0 1008 1.3863 0.0253
1.4022 17.0 1071 1.3863 0.1970
1.4022 18.0 1134 1.3863 0.0
1.4022 19.0 1197 1.3863 0.0909
1.4022 20.0 1260 1.3863 0.0505

Framework versions

  • Transformers 4.34.0.dev0
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.5
  • Tokenizers 0.14.0