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-qnli
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: GLUE QNLI
          type: glue
          args: qnli
        metrics:
          - type: accuracy
            value: 0.9125022881200805
            name: Accuracy

bert-base-uncased-qnli

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

Loss: 0.3208
Accuracy: 0.9125

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
0.289	1.0	3274	0.2289	0.9094
0.1801	2.0	6548	0.2493	0.9118
0.1074	3.0	9822	0.3208	0.9125

Framework versions

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