metadata

language:
  - en
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
  - f1
model-index:
  - name: mobilebert_sa_GLUE_Experiment_qqp_256
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE QQP
          type: glue
          config: qqp
          split: validation
          args: qqp
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.7976007914914668
          - name: F1
            type: f1
            value: 0.7297109826589595

mobilebert_sa_GLUE_Experiment_qqp_256

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

Loss: 0.4349
Accuracy: 0.7976
F1: 0.7297
Combined Score: 0.7637

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: 5e-05
train_batch_size: 128
eval_batch_size: 128
seed: 10
distributed_type: multi-GPU
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Combined Score
0.526	1.0	2843	0.5088	0.7492	0.6674	0.7083
0.4762	2.0	5686	0.4782	0.7695	0.6583	0.7139
0.4438	3.0	8529	0.4532	0.7847	0.6829	0.7338
0.4161	4.0	11372	0.4602	0.7869	0.7135	0.7502
0.3968	5.0	14215	0.4395	0.7955	0.7212	0.7583
0.3815	6.0	17058	0.4392	0.7985	0.7190	0.7587
0.3659	7.0	19901	0.4349	0.7976	0.7297	0.7637
0.352	8.0	22744	0.4419	0.8005	0.7300	0.7652
0.3399	9.0	25587	0.4454	0.7998	0.7317	0.7658
0.327	10.0	28430	0.4614	0.7995	0.7359	0.7677
0.3157	11.0	31273	0.4733	0.8000	0.7246	0.7623
0.3041	12.0	34116	0.4738	0.8041	0.7283	0.7662

Framework versions

Transformers 4.26.0
Pytorch 1.14.0a0+410ce96
Datasets 2.8.0
Tokenizers 0.13.2