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# cola

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the GLUE COLA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7272
- Matthews Correlation: 0.5660

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0

### Training results



### Framework versions

- Transformers 4.23.1
- Pytorch 1.12.1
- Datasets 2.6.1
- Tokenizers 0.13.1

{"language": ["en"], "license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["glue"], "metrics": ["matthews_correlation"], "model-index": [{"name": "cola", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "GLUE COLA", "type": "glue", "args": "cola"}, "metrics": [{"type": "matthews_correlation", "value": 0.565965534490769, "name": "Matthews Correlation"}]}]}]}
transformers pytorch bert text-classification generated_from_trainer en dataset:glue license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #en #dataset-glue #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 




# cola

This model is a fine-tuned version of bert-base-uncased on the GLUE COLA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7272
- Matthews Correlation: 0.5660

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0

### Training results



### Framework versions

- Transformers 4.23.1
- Pytorch 1.12.1
- Datasets 2.6.1
- Tokenizers 0.13.1

# cola

This model is a fine-tuned version of bert-base-uncased on the GLUE COLA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7272
- Matthews Correlation: 0.5660 ## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0 ### Training results ### Framework versions

- Transformers 4.23.1
- Pytorch 1.12.1
- Datasets 2.6.1
- Tokenizers 0.13.1
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #en #dataset-glue #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 # cola

This model is a fine-tuned version of bert-base-uncased on the GLUE COLA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7272
- Matthews Correlation: 0.5660 ## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0 ### Training results ### Framework versions

- Transformers 4.23.1
- Pytorch 1.12.1
- Datasets 2.6.1
- Tokenizers 0.13.1
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #en #dataset-glue #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
# cola

This model is a fine-tuned version of bert-base-uncased on the GLUE COLA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7272
- Matthews Correlation: 0.5660## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0### Training results### Framework versions

- Transformers 4.23.1
- Pytorch 1.12.1
- Datasets 2.6.1
- Tokenizers 0.13.1