metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
  - f1
model-index:
  - name: glue-qqp
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: glue
          type: glue
          args: qqp
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9033391046252782
          - name: F1
            type: f1
            value: 0.8703384207033842

glue-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: 0.4798
Accuracy: 0.9033
F1: 0.8703

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
0.2779	1.0	22741	0.2697	0.8871	0.8494
0.2183	2.0	45482	0.2651	0.8966	0.8634
0.1635	3.0	68223	0.3116	0.9013	0.8685
0.1312	4.0	90964	0.4102	0.9030	0.8694
0.0802	5.0	113705	0.4798	0.9033	0.8703

Framework versions

Transformers 4.20.1
Pytorch 1.11.0
Datasets 2.3.2
Tokenizers 0.11.6