---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: mobilebert_add_GLUE_Experiment_qqp
  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: 0.7599802127133317
    - name: F1
      type: f1
      value: 0.6401928068223952
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# mobilebert_add_GLUE_Experiment_qqp

This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5008
- Accuracy: 0.7600
- F1: 0.6402
- Combined Score: 0.7001

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6505        | 1.0   | 2843  | 0.6498          | 0.6321   | 0.0012 | 0.3166         |
| 0.6474        | 2.0   | 5686  | 0.6484          | 0.6321   | 0.0012 | 0.3166         |
| 0.646         | 3.0   | 8529  | 0.6479          | 0.6322   | 0.0024 | 0.3173         |
| 0.5481        | 4.0   | 11372 | 0.5140          | 0.7486   | 0.6247 | 0.6867         |
| 0.4934        | 5.0   | 14215 | 0.5086          | 0.7529   | 0.6548 | 0.7039         |
| 0.4794        | 6.0   | 17058 | 0.5044          | 0.7575   | 0.6527 | 0.7051         |
| 0.4708        | 7.0   | 19901 | 0.5008          | 0.7600   | 0.6402 | 0.7001         |
| 0.4652        | 8.0   | 22744 | 0.5010          | 0.7619   | 0.6384 | 0.7001         |
| 0.4604        | 9.0   | 25587 | 0.5014          | 0.7614   | 0.6489 | 0.7052         |
| 0.4562        | 10.0  | 28430 | 0.5057          | 0.7600   | 0.6617 | 0.7108         |
| 0.452         | 11.0  | 31273 | 0.5102          | 0.7620   | 0.6364 | 0.6992         |
| 0.4476        | 12.0  | 34116 | 0.5302          | 0.7622   | 0.6619 | 0.7121         |


### Framework versions

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