---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: mobilebert_sa_GLUE_Experiment_stsb_128
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE STSB
      type: glue
      config: stsb
      split: validation
      args: stsb
    metrics:
    - name: Spearmanr
      type: spearmanr
      value: 0.22304777472582654
---

<!-- 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_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: 2.2718
- Pearson: 0.2225
- Spearmanr: 0.2230
- Combined Score: 0.2228

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 5.1866        | 1.0   | 45   | 2.5161          | -0.0355 | -0.0329   | -0.0342        |
| 2.1786        | 2.0   | 90   | 2.3527          | 0.0407  | 0.0395    | 0.0401         |
| 2.1136        | 3.0   | 135  | 2.3101          | 0.0543  | 0.0555    | 0.0549         |
| 2.1           | 4.0   | 180  | 2.4469          | 0.0624  | 0.0656    | 0.0640         |
| 1.9564        | 5.0   | 225  | 2.8646          | 0.0815  | 0.0817    | 0.0816         |
| 1.8611        | 6.0   | 270  | 2.5597          | 0.1089  | 0.1054    | 0.1071         |
| 1.6702        | 7.0   | 315  | 2.7087          | 0.1644  | 0.1666    | 0.1655         |
| 1.385         | 8.0   | 360  | 2.2718          | 0.2225  | 0.2230    | 0.2228         |
| 1.2518        | 9.0   | 405  | 2.4105          | 0.2134  | 0.2022    | 0.2078         |
| 1.143         | 10.0  | 450  | 2.5834          | 0.1998  | 0.2083    | 0.2040         |
| 1.0191        | 11.0  | 495  | 2.6132          | 0.1856  | 0.1896    | 0.1876         |
| 0.9431        | 12.0  | 540  | 2.8187          | 0.1784  | 0.1872    | 0.1828         |
| 0.8725        | 13.0  | 585  | 2.8360          | 0.1815  | 0.1879    | 0.1847         |


### Framework versions

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