metadata

language:
  - en
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
base_model: bert-base-uncased
model-index:
  - name: bert-base-uncased-wnli
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: GLUE WNLI
          type: glue
          args: wnli
        metrics:
          - type: accuracy
            value: 0.5633802816901409
            name: Accuracy

bert-base-uncased-wnli

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

Loss: 0.6959
Accuracy: 0.5634

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
No log	1.0	20	0.6933	0.5493
No log	2.0	40	0.6959	0.5634
No log	3.0	60	0.6978	0.5352

Framework versions

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