---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: mobilebert_add_GLUE_Experiment_logit_kd_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: 0.041438738522880283
---

<!-- 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_logit_kd_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: 1.1505
- Pearson: 0.0470
- Spearmanr: 0.0414
- Combined Score: 0.0442

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.524         | 1.0   | 45   | 1.3607          | -0.0066 | -0.0281   | -0.0174        |
| 1.0877        | 2.0   | 90   | 1.1729          | 0.0446  | 0.0497    | 0.0472         |
| 1.0648        | 3.0   | 135  | 1.1505          | 0.0470  | 0.0414    | 0.0442         |
| 1.0737        | 4.0   | 180  | 1.1564          | 0.0472  | 0.0464    | 0.0468         |
| 1.0445        | 5.0   | 225  | 1.1971          | 0.0529  | 0.0575    | 0.0552         |
| 1.0296        | 6.0   | 270  | 1.1723          | 0.0578  | 0.0727    | 0.0652         |
| 1.026         | 7.0   | 315  | 1.2735          | 0.0621  | 0.0606    | 0.0614         |
| 1.0216        | 8.0   | 360  | 1.2214          | 0.0666  | 0.0700    | 0.0683         |


### Framework versions

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