metadata

library_name: transformers
language:
  - en
license: apache-2.0
base_model: bert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
  - f1
model-index:
  - name: bert-base-cased-finetuned-qqp
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE QQP
          type: glue
          args: qqp
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9108830076675736
          - name: F1
            type: f1
            value: 0.8798719701263629

bert-base-cased-finetuned-qqp

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

Loss: 0.3636
Accuracy: 0.9109
F1: 0.8799
Combined Score: 0.8954

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	Combined Score	F1	Validation Loss
0.2942	1.0	22741	0.9009	0.8845	0.8681	0.2476
0.1919	2.0	45482	0.9080	0.8920	0.8761	0.2706
0.1342	3.0	68223	0.9109	0.8957	0.8805	0.3568

Framework versions

Transformers 4.45.0.dev0
Pytorch 2.3.0+cu121
Datasets 2.18.0
Tokenizers 0.19.1