---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: mobilebert_sa_GLUE_Experiment_mnli
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE MNLI
      type: glue
      config: mnli
      split: validation_matched
      args: mnli
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6110659072416599
---

<!-- 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_sa_GLUE_Experiment_mnli

This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the GLUE MNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8609
- Accuracy: 0.6111

## 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.9907        | 1.0   | 3068  | 0.9408          | 0.5485   |
| 0.9094        | 2.0   | 6136  | 0.9065          | 0.5819   |
| 0.8828        | 3.0   | 9204  | 0.8969          | 0.5874   |
| 0.8627        | 4.0   | 12272 | 0.8821          | 0.5967   |
| 0.8429        | 5.0   | 15340 | 0.8743          | 0.6003   |
| 0.8207        | 6.0   | 18408 | 0.8663          | 0.6077   |
| 0.7989        | 7.0   | 21476 | 0.8665          | 0.6100   |
| 0.7789        | 8.0   | 24544 | 0.8751          | 0.6096   |
| 0.7603        | 9.0   | 27612 | 0.8620          | 0.6139   |
| 0.7425        | 10.0  | 30680 | 0.8813          | 0.6095   |
| 0.7238        | 11.0  | 33748 | 0.8913          | 0.6142   |
| 0.7063        | 12.0  | 36816 | 0.9026          | 0.6056   |
| 0.6891        | 13.0  | 39884 | 0.9267          | 0.5976   |
| 0.6721        | 14.0  | 42952 | 0.9072          | 0.6105   |


### Framework versions

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