
<!-- 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. -->

# xtremedistil-l12-h384-uncased-CoLA

This model is a fine-tuned version of [microsoft/xtremedistil-l12-h384-uncased](https://huggingface.co/microsoft/xtremedistil-l12-h384-uncased) on the GLUE COLA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4974
- Matthews Correlation: 0.5396

## 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: 0.0001
- train_batch_size: 128
- eval_batch_size: 16
- seed: 5559
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 16.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|
| 0.4822        | 1.0   | 67   | 0.5893          | 0.2621               |
| 0.4669        | 2.0   | 134  | 0.5811          | 0.3722               |
| 0.3077        | 3.0   | 201  | 0.6150          | 0.4383               |
| 0.2594        | 4.0   | 268  | 0.4974          | 0.5396               |
| 0.21          | 5.0   | 335  | 0.5594          | 0.5182               |
| 0.1526        | 6.0   | 402  | 0.5715          | 0.5150               |
| 0.1775        | 7.0   | 469  | 0.6637          | 0.5020               |
| 0.1681        | 8.0   | 536  | 0.6958          | 0.5131               |
| 0.124         | 9.0   | 603  | 0.7057          | 0.5154               |
| 0.1111        | 10.0  | 670  | 0.8173          | 0.5074               |
| 0.1332        | 11.0  | 737  | 0.8253          | 0.5260               |
| 0.0673        | 12.0  | 804  | 0.8086          | 0.5180               |
| 0.0512        | 13.0  | 871  | 0.8409          | 0.5128               |
| 0.0457        | 14.0  | 938  | 0.8760          | 0.4947               |
| 0.04          | 15.0  | 1005 | 0.8522          | 0.5103               |
| 0.0485        | 16.0  | 1072 | 0.8556          | 0.5076               |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.1

{"language": ["en"], "license": "mit", "tags": ["generated_from_trainer"], "datasets": ["glue"], "metrics": ["matthews_correlation"], "widget": [{"text": "The cat sat on the mat.", "example_title": "Correct grammatical sentence"}, {"text": "Me and my friend going to the store.", "example_title": "Incorrect subject-verb agreement"}, {"text": "I ain't got no money.", "example_title": "Incorrect verb conjugation and double negative"}, {"text": "She don't like pizza no more.", "example_title": "Incorrect verb conjugation and double negative"}, {"text": "They is arriving tomorrow.", "example_title": "Incorrect verb conjugation"}], "model-index": [{"name": "xtremedistil-l12-h384-uncased-CoLA", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "GLUE COLA", "type": "glue", "config": "cola", "split": "validation", "args": "cola"}, "metrics": [{"type": "matthews_correlation", "value": 0.5395539646127814, "name": "Matthews Correlation"}]}]}]}
transformers pytorch onnx bert text-classification generated_from_trainer en dataset:glue license:mit model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #onnx #bert #text-classification #generated_from_trainer #en #dataset-glue #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 

xtremedistil-l12-h384-uncased-CoLA
==================================


This model is a fine-tuned version of microsoft/xtremedistil-l12-h384-uncased on the GLUE COLA dataset.
It achieves the following results on the evaluation set:


* Loss: 0.4974
* Matthews Correlation: 0.5396


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: 0.0001
* train\_batch\_size: 128
* eval\_batch\_size: 16
* seed: 5559
* distributed\_type: multi-GPU
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_ratio: 0.03
* num\_epochs: 16.0
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1+cu117
* Datasets 2.8.0
* Tokenizers 0.13.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 128
* eval\_batch\_size: 16
* seed: 5559
* distributed\_type: multi-GPU
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_ratio: 0.03
* num\_epochs: 16.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1+cu117
* Datasets 2.8.0
* Tokenizers 0.13.1
TAGS
#transformers #pytorch #onnx #bert #text-classification #generated_from_trainer #en #dataset-glue #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 128
* eval\_batch\_size: 16
* seed: 5559
* distributed\_type: multi-GPU
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_ratio: 0.03
* num\_epochs: 16.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1+cu117
* Datasets 2.8.0
* Tokenizers 0.13.1
TAGS
#transformers #pytorch #onnx #bert #text-classification #generated_from_trainer #en #dataset-glue #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 128
* eval\_batch\_size: 16
* seed: 5559
* distributed\_type: multi-GPU
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_ratio: 0.03
* num\_epochs: 16.0
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1+cu117
* Datasets 2.8.0
* Tokenizers 0.13.1