transformers pytorch tensorboard mobilebert text-classification generated_from_trainer en dataset:glue license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- glue
language:
- en
license: apache-2.0
metrics:
- spearmanr
tags:
- generated_from_trainer
model-index:
- name: mobilebert_sa_GLUE_Experiment_data_aug_stsb
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE STSB
      type: glue
      args: stsb
    metrics:
    - type: spearmanr
      value: 0.17999491409200302
      name: Spearmanr
---

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# mobilebert_sa_GLUE_Experiment_data_aug_stsb

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: 2.8342
- Pearson: 0.1765
- Spearmanr: 0.1800
- Combined Score: 0.1782

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:---------:|:--------------:|
| 1.0254        | 1.0   | 2518  | 2.8776          | 0.1575  | 0.1742    | 0.1659         |
| 0.5854        | 2.0   | 5036  | 3.1464          | 0.1591  | 0.1679    | 0.1635         |
| 0.4255        | 3.0   | 7554  | 2.8342          | 0.1765  | 0.1800    | 0.1782         |
| 0.2765        | 4.0   | 10072 | 2.8524          | 0.1815  | 0.1838    | 0.1827         |
| 0.1862        | 5.0   | 12590 | 2.9184          | 0.1736  | 0.1768    | 0.1752         |
| 0.1339        | 6.0   | 15108 | 2.9817          | 0.1688  | 0.1728    | 0.1708         |
| 0.1029        | 7.0   | 17626 | 2.9702          | 0.1618  | 0.1643    | 0.1631         |
| 0.0806        | 8.0   | 20144 | 3.0033          | 0.1588  | 0.1624    | 0.1606         |


### Framework versions

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