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_logit_kd_pretrain_wnli
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE WNLI
      type: glue
      config: wnli
      split: validation
      args: wnli
    metrics:
    - type: accuracy
      value: 0.29577464788732394
      name: Accuracy
---

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# mobilebert_sa_GLUE_Experiment_logit_kd_pretrain_wnli

This model is a fine-tuned version of [gokuls/mobilebert_sa_pre-training-complete](https://huggingface.co/gokuls/mobilebert_sa_pre-training-complete) on the GLUE WNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3677
- Accuracy: 0.2958

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3708        | 1.0   | 5    | 0.3927          | 0.3944   |
| 0.3555        | 2.0   | 10   | 0.3715          | 0.4225   |
| 0.3493        | 3.0   | 15   | 0.3677          | 0.2958   |
| 0.3485        | 4.0   | 20   | 0.3704          | 0.3803   |
| 0.3454        | 5.0   | 25   | 0.3815          | 0.2394   |
| 0.3461        | 6.0   | 30   | 0.3878          | 0.2394   |
| 0.3432        | 7.0   | 35   | 0.3962          | 0.2535   |
| 0.3427        | 8.0   | 40   | 0.4050          | 0.1972   |


### Framework versions

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