---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: mobilebert_sa_GLUE_Experiment_data_aug_stsb_128
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE STSB
      type: glue
      args: stsb
    metrics:
    - name: Spearmanr
      type: spearmanr
      value: 0.19841990187987396
---

<!-- 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_sa_GLUE_Experiment_data_aug_stsb_128

This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7704
- Pearson: 0.1811
- Spearmanr: 0.1984
- Combined Score: 0.1898

## 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 | Pearson | Spearmanr | Combined Score |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:---------:|:--------------:|
| 1.1017        | 1.0   | 2518  | 2.7704          | 0.1811  | 0.1984    | 0.1898         |
| 0.654         | 2.0   | 5036  | 3.0506          | 0.1580  | 0.1703    | 0.1642         |
| 0.5737        | 3.0   | 7554  | 3.1679          | 0.1482  | 0.1569    | 0.1526         |
| 0.4954        | 4.0   | 10072 | 3.3175          | 0.1564  | 0.1617    | 0.1590         |
| 0.3722        | 5.0   | 12590 | 2.9558          | 0.1426  | 0.1517    | 0.1471         |
| 0.276         | 6.0   | 15108 | 3.2021          | 0.1462  | 0.1530    | 0.1496         |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.9.0
- Tokenizers 0.13.2