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# mobilebert_sa_GLUE_Experiment_logit_kd_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: 0.1267
- Accuracy: 0.9926
- F1: 0.9947
- Combined Score: 0.9936

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.3017        | 1.0   | 1959  | 0.2241          | 0.9608   | 0.9713 | 0.9661         |
| 0.233         | 2.0   | 3918  | 0.2357          | 0.9828   | 0.9876 | 0.9852         |
| 0.2241        | 3.0   | 5877  | 0.1908          | 0.9706   | 0.9786 | 0.9746         |
| 0.2189        | 4.0   | 7836  | 0.1863          | 0.9755   | 0.9824 | 0.9789         |
| 0.2149        | 5.0   | 9795  | 0.1868          | 0.9804   | 0.9858 | 0.9831         |
| 0.211         | 6.0   | 11754 | 0.1735          | 0.9804   | 0.9859 | 0.9831         |
| 0.2073        | 7.0   | 13713 | 0.1875          | 0.9828   | 0.9876 | 0.9852         |
| 0.204         | 8.0   | 15672 | 0.1690          | 0.9853   | 0.9894 | 0.9873         |
| 0.2014        | 9.0   | 17631 | 0.1597          | 0.9853   | 0.9893 | 0.9873         |
| 0.1992        | 10.0  | 19590 | 0.1604          | 0.9877   | 0.9911 | 0.9894         |
| 0.1975        | 11.0  | 21549 | 0.1563          | 0.9853   | 0.9894 | 0.9873         |
| 0.1959        | 12.0  | 23508 | 0.1518          | 0.9853   | 0.9894 | 0.9873         |
| 0.1948        | 13.0  | 25467 | 0.1429          | 0.9902   | 0.9929 | 0.9915         |
| 0.1937        | 14.0  | 27426 | 0.1484          | 0.9853   | 0.9894 | 0.9873         |
| 0.1928        | 15.0  | 29385 | 0.1527          | 0.9804   | 0.9856 | 0.9830         |
| 0.1919        | 16.0  | 31344 | 0.1433          | 0.9926   | 0.9947 | 0.9936         |
| 0.1913        | 17.0  | 33303 | 0.1445          | 0.9902   | 0.9929 | 0.9915         |
| 0.1905        | 18.0  | 35262 | 0.1407          | 0.9926   | 0.9947 | 0.9936         |
| 0.1899        | 19.0  | 37221 | 0.1402          | 0.9926   | 0.9947 | 0.9936         |
| 0.1892        | 20.0  | 39180 | 0.1387          | 0.9926   | 0.9947 | 0.9936         |
| 0.1887        | 21.0  | 41139 | 0.1384          | 0.9926   | 0.9947 | 0.9936         |
| 0.1882        | 22.0  | 43098 | 0.1430          | 0.9951   | 0.9964 | 0.9958         |
| 0.1877        | 23.0  | 45057 | 0.1384          | 0.9951   | 0.9964 | 0.9958         |
| 0.1871        | 24.0  | 47016 | 0.1398          | 0.9951   | 0.9964 | 0.9958         |
| 0.1867        | 25.0  | 48975 | 0.1336          | 0.9926   | 0.9947 | 0.9936         |
| 0.1863        | 26.0  | 50934 | 0.1368          | 0.9951   | 0.9964 | 0.9958         |
| 0.1859        | 27.0  | 52893 | 0.1337          | 0.9951   | 0.9964 | 0.9958         |
| 0.1855        | 28.0  | 54852 | 0.1352          | 0.9926   | 0.9947 | 0.9936         |
| 0.1851        | 29.0  | 56811 | 0.1314          | 0.9951   | 0.9964 | 0.9958         |
| 0.1847        | 30.0  | 58770 | 0.1333          | 0.9951   | 0.9964 | 0.9958         |
| 0.1844        | 31.0  | 60729 | 0.1368          | 0.9951   | 0.9964 | 0.9958         |
| 0.184         | 32.0  | 62688 | 0.1310          | 0.9951   | 0.9964 | 0.9958         |
| 0.1837        | 33.0  | 64647 | 0.1321          | 0.9951   | 0.9964 | 0.9958         |
| 0.1834        | 34.0  | 66606 | 0.1302          | 0.9926   | 0.9947 | 0.9936         |
| 0.183         | 35.0  | 68565 | 0.1320          | 0.9951   | 0.9964 | 0.9958         |
| 0.1827        | 36.0  | 70524 | 0.1303          | 0.9951   | 0.9964 | 0.9958         |
| 0.1825        | 37.0  | 72483 | 0.1273          | 0.9951   | 0.9964 | 0.9958         |
| 0.1822        | 38.0  | 74442 | 0.1293          | 0.9951   | 0.9964 | 0.9958         |
| 0.1819        | 39.0  | 76401 | 0.1296          | 0.9951   | 0.9964 | 0.9958         |
| 0.1817        | 40.0  | 78360 | 0.1305          | 0.9926   | 0.9947 | 0.9936         |
| 0.1814        | 41.0  | 80319 | 0.1267          | 0.9926   | 0.9947 | 0.9936         |
| 0.1812        | 42.0  | 82278 | 0.1267          | 0.9951   | 0.9964 | 0.9958         |
| 0.1809        | 43.0  | 84237 | 0.1278          | 0.9902   | 0.9929 | 0.9915         |
| 0.1807        | 44.0  | 86196 | 0.1293          | 0.9951   | 0.9964 | 0.9958         |
| 0.1805        | 45.0  | 88155 | 0.1269          | 0.9951   | 0.9964 | 0.9958         |
| 0.1803        | 46.0  | 90114 | 0.1284          | 0.9951   | 0.9964 | 0.9958         |


### Framework versions

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

{"language": ["en"], "license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["glue"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "mobilebert_sa_GLUE_Experiment_logit_kd_data_aug_mrpc_256", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "GLUE MRPC", "type": "glue", "args": "mrpc"}, "metrics": [{"type": "accuracy", "value": 0.9926470588235294, "name": "Accuracy"}, {"type": "f1", "value": 0.9946524064171123, "name": "F1"}]}]}]}
transformers pytorch tensorboard mobilebert text-classification generated_from_trainer en dataset:glue license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #mobilebert #text-classification #generated_from_trainer #en #dataset-glue #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

mobilebert\_sa\_GLUE\_Experiment\_logit\_kd\_data\_aug\_mrpc\_256
=================================================================


This model is a fine-tuned version of google/mobilebert-uncased on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1267
* Accuracy: 0.9926
* F1: 0.9947
* Combined Score: 0.9936


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



### Framework versions


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



### 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 ### Framework versions


* Transformers 4.26.0
* Pytorch 1.14.0a0+410ce96
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #mobilebert #text-classification #generated_from_trainer #en #dataset-glue #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### 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 ### Framework versions


* Transformers 4.26.0
* Pytorch 1.14.0a0+410ce96
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #mobilebert #text-classification #generated_from_trainer #en #dataset-glue #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
### 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### Framework versions


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