---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: mobilebert_add_GLUE_Experiment_mrpc_256
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE MRPC
      type: glue
      config: mrpc
      split: validation
      args: mrpc
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6838235294117647
    - name: F1
      type: f1
      value: 0.8122270742358079
---

<!-- 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_mrpc_256

This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6207
- Accuracy: 0.6838
- F1: 0.8122
- Combined Score: 0.7480

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6419        | 1.0   | 29   | 0.6266          | 0.6838   | 0.8122 | 0.7480         |
| 0.6297        | 2.0   | 58   | 0.6236          | 0.6838   | 0.8122 | 0.7480         |
| 0.6307        | 3.0   | 87   | 0.6241          | 0.6838   | 0.8122 | 0.7480         |
| 0.63          | 4.0   | 116  | 0.6243          | 0.6838   | 0.8122 | 0.7480         |
| 0.6283        | 5.0   | 145  | 0.6219          | 0.6838   | 0.8122 | 0.7480         |
| 0.6243        | 6.0   | 174  | 0.6207          | 0.6838   | 0.8122 | 0.7480         |
| 0.6206        | 7.0   | 203  | 0.6346          | 0.6838   | 0.8122 | 0.7480         |
| 0.6034        | 8.0   | 232  | 0.6519          | 0.6348   | 0.7545 | 0.6947         |
| 0.5877        | 9.0   | 261  | 0.6375          | 0.6838   | 0.8122 | 0.7480         |
| 0.5722        | 10.0  | 290  | 0.6446          | 0.6299   | 0.7504 | 0.6902         |
| 0.5619        | 11.0  | 319  | 0.6733          | 0.6814   | 0.8105 | 0.7459         |


### Framework versions

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