---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: mobilebert_sa_GLUE_Experiment_logit_kd_data_aug_qnli
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE QNLI
      type: glue
      args: qnli
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.5923485264506682
---

<!-- 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_logit_kd_data_aug_qnli

This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the GLUE QNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1420
- Accuracy: 0.5923

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 0.6899        | 1.0   | 33208  | 1.1420          | 0.5923   |
| 0.498         | 2.0   | 66416  | 1.2196          | 0.5944   |
| 0.4209        | 3.0   | 99624  | 1.2370          | 0.5977   |
| 0.3746        | 4.0   | 132832 | 1.2784          | 0.5973   |
| 0.3449        | 5.0   | 166040 | 1.2649          | 0.5938   |
| 0.3238        | 6.0   | 199248 | 1.1662          | 0.6114   |


### Framework versions

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