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_logit_kd_data_aug_stsb_128
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE STSB
      type: glue
      args: stsb
    metrics:
    - type: spearmanr
      value: 0.15823601400463258
      name: Spearmanr
---

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# mobilebert_sa_GLUE_Experiment_logit_kd_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: 1.4602
- Pearson: 0.1596
- Spearmanr: 0.1582
- Combined Score: 0.1589

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:---------:|:--------------:|
| 0.5444        | 1.0   | 2518  | 1.4965          | 0.1589  | 0.1763    | 0.1676         |
| 0.3254        | 2.0   | 5036  | 1.5276          | 0.1502  | 0.1674    | 0.1588         |
| 0.2847        | 3.0   | 7554  | 1.5430          | 0.1587  | 0.1680    | 0.1634         |
| 0.2376        | 4.0   | 10072 | 1.6906          | 0.1669  | 0.1786    | 0.1728         |
| 0.1741        | 5.0   | 12590 | 1.4788          | 0.1662  | 0.1725    | 0.1694         |
| 0.1315        | 6.0   | 15108 | 1.5662          | 0.1640  | 0.1700    | 0.1670         |
| 0.1055        | 7.0   | 17626 | 1.5100          | 0.1663  | 0.1698    | 0.1680         |
| 0.0879        | 8.0   | 20144 | 1.4602          | 0.1596  | 0.1582    | 0.1589         |
| 0.0739        | 9.0   | 22662 | 1.6612          | 0.1584  | 0.1621    | 0.1603         |
| 0.0632        | 10.0  | 25180 | 1.5825          | 0.1489  | 0.1547    | 0.1518         |
| 0.0548        | 11.0  | 27698 | 1.5946          | 0.1421  | 0.1461    | 0.1441         |
| 0.0473        | 12.0  | 30216 | 1.6515          | 0.1526  | 0.1548    | 0.1537         |
| 0.0415        | 13.0  | 32734 | 1.6544          | 0.1506  | 0.1478    | 0.1492         |


### Framework versions

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