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# bert-base-uncased-finetuned-cola_HW2_sepehr_bakhshi_dropout_05

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4260
- Matthews Correlation: 0.5780

## 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: 7.530341440816975e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Matthews Correlation |
|:-------------:|:-----:|:-----:|:---------------:|:--------------------:|
| 0.5137        | 1.0   | 535   | 0.4936          | 0.4808               |
| 0.362         | 2.0   | 1070  | 0.4270          | 0.5781               |
| 0.2679        | 3.0   | 1605  | 0.6409          | 0.5148               |
| 0.2046        | 4.0   | 2140  | 0.5658          | 0.5892               |
| 0.1736        | 5.0   | 2675  | 0.7711          | 0.5624               |
| 0.1378        | 6.0   | 3210  | 0.8053          | 0.5956               |
| 0.1137        | 7.0   | 3745  | 0.9714          | 0.5523               |
| 0.0903        | 8.0   | 4280  | 0.9119          | 0.5735               |
| 0.0839        | 9.0   | 4815  | 1.0448          | 0.5839               |
| 0.0629        | 10.0  | 5350  | 1.2056          | 0.5521               |
| 0.0577        | 11.0  | 5885  | 1.1880          | 0.5889               |
| 0.0505        | 12.0  | 6420  | 1.1722          | 0.5836               |
| 0.0519        | 13.0  | 6955  | 1.2863          | 0.5884               |
| 0.0369        | 14.0  | 7490  | 1.2971          | 0.5608               |
| 0.032         | 15.0  | 8025  | 1.3024          | 0.5785               |
| 0.0244        | 16.0  | 8560  | 1.3904          | 0.5737               |
| 0.0166        | 17.0  | 9095  | 1.4044          | 0.5778               |
| 0.0185        | 18.0  | 9630  | 1.4234          | 0.5650               |
| 0.0168        | 19.0  | 10165 | 1.4384          | 0.5727               |
| 0.0224        | 20.0  | 10700 | 1.4260          | 0.5780               |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["glue"], "metrics": ["matthews_correlation"], "model-index": [{"name": "bert-base-uncased-finetuned-cola_HW2_sepehr_bakhshi_dropout_05", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "glue", "type": "glue", "config": "cola", "split": "validation", "args": "cola"}, "metrics": [{"type": "matthews_correlation", "value": 0.5779953180551635, "name": "Matthews Correlation"}]}]}]}
transformers pytorch tensorboard bert text-classification generated_from_trainer dataset:glue license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #dataset-glue #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

bert-base-uncased-finetuned-cola\_HW2\_sepehr\_bakhshi\_dropout\_05
===================================================================


This model is a fine-tuned version of bert-base-uncased on the glue dataset.
It achieves the following results on the evaluation set:


* Loss: 1.4260
* Matthews Correlation: 0.5780


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: 7.530341440816975e-06
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 7.530341440816975e-06
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #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: 7.530341440816975e-06
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3