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_stsb_256
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE STSB
      type: glue
      config: stsb
      split: validation
      args: stsb
    metrics:
    - type: spearmanr
      value: 0.016625925233910453
      name: Spearmanr
---

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# mobilebert_sa_GLUE_Experiment_logit_kd_stsb_256

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: 1.1337
- Pearson: 0.0151
- Spearmanr: 0.0166
- Combined Score: 0.0159

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.075         | 1.0   | 45   | 1.1337          | 0.0151  | 0.0166    | 0.0159         |
| 1.0752        | 2.0   | 90   | 1.1691          | 0.0603  | 0.0648    | 0.0626         |
| 1.0435        | 3.0   | 135  | 1.2035          | 0.0659  | 0.0746    | 0.0703         |
| 1.0472        | 4.0   | 180  | 1.1488          | 0.0764  | 0.0817    | 0.0790         |
| 0.9687        | 5.0   | 225  | 1.5234          | 0.0979  | 0.0959    | 0.0969         |
| 0.9016        | 6.0   | 270  | 1.2243          | 0.1434  | 0.1381    | 0.1408         |


### Framework versions

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