metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
  - f1
model-index:
  - name: distilbert-base-uncased-finetuned-qqp
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: glue
          type: glue
          config: qqp
          split: validation
          args: qqp
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.90187979223349
          - name: F1
            type: f1
            value: 0.8681139665547393

distilbert-base-uncased-finetuned-qqp

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

Loss: 0.4957
Accuracy: 0.9019
F1: 0.8681

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: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.2846	1.0	22741	0.2751	0.8823	0.8451
0.2198	2.0	45482	0.2744	0.8989	0.8649
0.169	3.0	68223	0.3182	0.8993	0.8675
0.1281	4.0	90964	0.4432	0.9017	0.8688
0.0874	5.0	113705	0.4957	0.9019	0.8681

Framework versions

Transformers 4.27.4
Pytorch 2.0.0+cu118
Datasets 2.11.0
Tokenizers 0.13.3