---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: mobilebert_add_GLUE_Experiment_logit_kd_pretrain_mrpc
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE MRPC
      type: glue
      config: mrpc
      split: validation
      args: mrpc
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.3161764705882353
    - name: F1
      type: f1
      value: 0.0
---

<!-- 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_add_GLUE_Experiment_logit_kd_pretrain_mrpc

This model is a fine-tuned version of [gokuls/mobilebert_add_pre-training-complete](https://huggingface.co/gokuls/mobilebert_add_pre-training-complete) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Accuracy: 0.3162
- F1: 0.0
- Combined Score: 0.1581

## 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 | F1  | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---:|:--------------:|
| 0.0           | 1.0   | 29   | nan             | 0.3162   | 0.0 | 0.1581         |
| 0.0           | 2.0   | 58   | nan             | 0.3162   | 0.0 | 0.1581         |
| 0.0           | 3.0   | 87   | nan             | 0.3162   | 0.0 | 0.1581         |
| 0.0           | 4.0   | 116  | nan             | 0.3162   | 0.0 | 0.1581         |
| 0.0           | 5.0   | 145  | nan             | 0.3162   | 0.0 | 0.1581         |
| 0.0           | 6.0   | 174  | nan             | 0.3162   | 0.0 | 0.1581         |


### Framework versions

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