---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: mobilebert_sa_GLUE_Experiment_qnli
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE QNLI
      type: glue
      args: qnli
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6086399414241259
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# mobilebert_sa_GLUE_Experiment_qnli

This model is a fine-tuned version of [](https://huggingface.co/) on the GLUE QNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6524
- Accuracy: 0.6086

## 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: 256
- eval_batch_size: 256
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6824        | 1.0   | 410  | 0.6578          | 0.5997   |
| 0.6441        | 2.0   | 820  | 0.6524          | 0.6086   |
| 0.6202        | 3.0   | 1230 | 0.6554          | 0.6072   |
| 0.6009        | 4.0   | 1640 | 0.6619          | 0.6052   |
| 0.587         | 5.0   | 2050 | 0.6684          | 0.5986   |
| 0.5755        | 6.0   | 2460 | 0.6808          | 0.5978   |
| 0.5671        | 7.0   | 2870 | 0.7068          | 0.5845   |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.14.0a0+410ce96
- Datasets 2.8.0
- Tokenizers 0.13.2