Jeremiah Zhou
update model card README.md
54d18a6
|
raw
history blame
1.71 kB
metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: bert-base-uncased-mnli
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: glue
          type: glue
          args: mnli
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8445236882322975

bert-base-uncased-mnli

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

  • Loss: 0.4974
  • Accuracy: 0.8445

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: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3.0

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.4526 1.0 12272 0.4244 0.8388
0.3344 2.0 24544 0.4252 0.8469
0.2307 3.0 36816 0.4974 0.8445

Framework versions

  • Transformers 4.20.0.dev0
  • Pytorch 1.11.0+cu113
  • Datasets 2.1.0
  • Tokenizers 0.12.1