metadata

library_name: transformers
language:
  - en
license: apache-2.0
base_model: bert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: bert-base-uncased-finetuned-qnli
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE QNLI
          type: glue
          args: qnli
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9117700896943072

bert-base-uncased-finetuned-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: 0.4066
Accuracy: 0.9118

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: 16
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	Accuracy	Validation Loss
0.3365	1.0	6547	0.9065	0.2398
0.1938	2.0	13094	0.9109	0.2898
0.1171	3.0	19641	0.9132	0.3919

Framework versions

Transformers 4.45.0.dev0
Pytorch 2.4.1+cu121
Datasets 3.0.0
Tokenizers 0.19.1