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_add_GLUE_Experiment_stsb
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE STSB
      type: glue
      config: stsb
      split: validation
      args: stsb
    metrics:
    - type: spearmanr
      value: 0.08315656124877865
      name: Spearmanr
---

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# mobilebert_add_GLUE_Experiment_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: 2.3720
- Pearson: 0.0872
- Spearmanr: 0.0832
- Combined Score: 0.0852

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 3.5023        | 1.0   | 45   | 2.4151          | 0.0290  | 0.0235    | 0.0262         |
| 2.148         | 2.0   | 90   | 2.4051          | 0.0483  | 0.0436    | 0.0460         |
| 2.1403        | 3.0   | 135  | 2.7281          | 0.0523  | 0.0502    | 0.0513         |
| 2.0908        | 4.0   | 180  | 2.5970          | 0.0511  | 0.0509    | 0.0510         |
| 2.0699        | 5.0   | 225  | 2.5728          | 0.0601  | 0.0621    | 0.0611         |
| 2.0307        | 6.0   | 270  | 2.4059          | 0.0700  | 0.0781    | 0.0740         |
| 1.9823        | 7.0   | 315  | 2.3720          | 0.0872  | 0.0832    | 0.0852         |
| 1.9283        | 8.0   | 360  | 2.4539          | 0.0836  | 0.0814    | 0.0825         |
| 1.9014        | 9.0   | 405  | 2.3975          | 0.0950  | 0.0915    | 0.0932         |
| 1.883         | 10.0  | 450  | 2.6096          | 0.0894  | 0.0876    | 0.0885         |
| 1.8453        | 11.0  | 495  | 2.4121          | 0.0970  | 0.0912    | 0.0941         |
| 1.8275        | 12.0  | 540  | 2.6028          | 0.1038  | 0.0920    | 0.0979         |


### Framework versions

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