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---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: mobilebert_sa_GLUE_Experiment_data_aug_mrpc_256
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
type: glue
args: mrpc
metrics:
- name: Accuracy
type: accuracy
value: 1.0
- name: F1
type: f1
value: 1.0
---
<!-- 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_sa_GLUE_Experiment_data_aug_mrpc_256
This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Accuracy: 1.0
- F1: 1.0
- Combined Score: 1.0
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.1854 | 1.0 | 1959 | 0.0199 | 0.9975 | 0.9982 | 0.9979 |
| 0.04 | 2.0 | 3918 | 0.0050 | 0.9975 | 0.9982 | 0.9979 |
| 0.0253 | 3.0 | 5877 | 0.0015 | 1.0 | 1.0 | 1.0 |
| 0.0175 | 4.0 | 7836 | 0.0003 | 1.0 | 1.0 | 1.0 |
| 0.0134 | 5.0 | 9795 | 0.0001 | 1.0 | 1.0 | 1.0 |
| 0.0107 | 6.0 | 11754 | 0.0001 | 1.0 | 1.0 | 1.0 |
| 0.0081 | 7.0 | 13713 | 0.0012 | 1.0 | 1.0 | 1.0 |
| 0.0062 | 8.0 | 15672 | 0.0000 | 1.0 | 1.0 | 1.0 |
| 0.0061 | 9.0 | 17631 | 0.0001 | 1.0 | 1.0 | 1.0 |
| 0.0044 | 10.0 | 19590 | 0.0002 | 1.0 | 1.0 | 1.0 |
| 0.0041 | 11.0 | 21549 | 0.0000 | 1.0 | 1.0 | 1.0 |
| 0.0034 | 12.0 | 23508 | 0.0000 | 1.0 | 1.0 | 1.0 |
| 0.0029 | 13.0 | 25467 | 0.0000 | 1.0 | 1.0 | 1.0 |
| 0.0016 | 14.0 | 27426 | 0.0000 | 1.0 | 1.0 | 1.0 |
| 0.0019 | 15.0 | 29385 | 0.0140 | 0.9975 | 0.9982 | 0.9979 |
| 0.0018 | 16.0 | 31344 | 0.0001 | 1.0 | 1.0 | 1.0 |
| 0.0012 | 17.0 | 33303 | 0.0000 | 1.0 | 1.0 | 1.0 |
| 0.0013 | 18.0 | 35262 | 0.0000 | 1.0 | 1.0 | 1.0 |
| 0.0008 | 19.0 | 37221 | 0.0000 | 1.0 | 1.0 | 1.0 |
| 0.0011 | 20.0 | 39180 | 0.0000 | 1.0 | 1.0 | 1.0 |
| 0.0005 | 21.0 | 41139 | 0.0007 | 1.0 | 1.0 | 1.0 |
| 0.0009 | 22.0 | 43098 | 0.0000 | 1.0 | 1.0 | 1.0 |
| 0.0004 | 23.0 | 45057 | 0.0000 | 1.0 | 1.0 | 1.0 |
| 0.0004 | 24.0 | 47016 | 0.0000 | 1.0 | 1.0 | 1.0 |
### Framework versions
- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.9.0
- Tokenizers 0.13.2
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