---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: mobilebert_add_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: 0.7558496166213208
    - name: F1
      type: f1
      value: 0.6390991188621988
---

<!-- 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_256

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: 0.5069
- Accuracy: 0.7558
- F1: 0.6391
- Combined Score: 0.6975

## 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  | 0.6497          | 0.6321   | 0.0012 | 0.3166         |
| 0.6473        | 2.0   | 5686  | 0.6479          | 0.6321   | 0.0012 | 0.3166         |
| 0.5376        | 3.0   | 8529  | 0.5167          | 0.7486   | 0.5879 | 0.6682         |
| 0.4943        | 4.0   | 11372 | 0.5069          | 0.7558   | 0.6391 | 0.6975         |
| 0.4816        | 5.0   | 14215 | 0.5072          | 0.7547   | 0.6574 | 0.7061         |
| 0.4738        | 6.0   | 17058 | nan             | 0.7588   | 0.6526 | 0.7057         |
| 0.4646        | 7.0   | 19901 | nan             | 0.6318   | 0.0    | 0.3159         |
| 0.0           | 8.0   | 22744 | nan             | 0.6318   | 0.0    | 0.3159         |
| 0.0           | 9.0   | 25587 | nan             | 0.6318   | 0.0    | 0.3159         |


### Framework versions

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