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:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: mobilebert_sa_GLUE_Experiment_data_aug_wnli_256
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE WNLI
      type: glue
      args: wnli
    metrics:
    - type: accuracy
      value: 0.15492957746478872
      name: Accuracy
---

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# mobilebert_sa_GLUE_Experiment_data_aug_wnli_256

This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the GLUE WNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3011
- Accuracy: 0.1549

## 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 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6528        | 1.0   | 435  | 2.3011          | 0.1549   |
| 0.4834        | 2.0   | 870  | 3.5400          | 0.0986   |
| 0.4353        | 3.0   | 1305 | 5.1022          | 0.1127   |
| 0.4022        | 4.0   | 1740 | 6.6353          | 0.1408   |
| 0.3757        | 5.0   | 2175 | 10.7943         | 0.0986   |
| 0.3399        | 6.0   | 2610 | 14.3396         | 0.0845   |


### Framework versions

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