---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: mobilebert_sa_GLUE_Experiment_mnli_256
  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: 0.6030309194467046
---

<!-- 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_256

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: 0.8790
- Accuracy: 0.6030

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.0008        | 1.0   | 3068  | 0.9490          | 0.5405   |
| 0.9205        | 2.0   | 6136  | 0.9166          | 0.5675   |
| 0.8928        | 3.0   | 9204  | 0.9022          | 0.5786   |
| 0.872         | 4.0   | 12272 | 0.8843          | 0.5967   |
| 0.8531        | 5.0   | 15340 | 0.8807          | 0.5959   |
| 0.8359        | 6.0   | 18408 | 0.8763          | 0.5999   |
| 0.8197        | 7.0   | 21476 | 0.8815          | 0.6009   |
| 0.8028        | 8.0   | 24544 | 0.9012          | 0.5934   |
| 0.786         | 9.0   | 27612 | 0.8633          | 0.6191   |
| 0.769         | 10.0  | 30680 | 0.8734          | 0.6098   |
| 0.752         | 11.0  | 33748 | 0.8682          | 0.6220   |
| 0.736         | 12.0  | 36816 | 0.8741          | 0.6175   |
| 0.7204        | 13.0  | 39884 | 0.8994          | 0.6048   |
| 0.7038        | 14.0  | 42952 | 0.8940          | 0.6079   |


### Framework versions

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