README.md

---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: bert-base-uncased-cola
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE COLA
      type: glue
      args: cola
    metrics:
    - name: Matthews Correlation
      type: matthews_correlation
      value: 0.5880094937717885
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: glue
      type: glue
      config: cola
      split: validation
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8322147651006712
      verified: true
    - name: Precision Macro
      type: precision
      value: 0.830203748981255
      verified: true
    - name: Precision Micro
      type: precision
      value: 0.8322147651006712
      verified: true
    - name: Precision Weighted
      type: precision
      value: 0.8315568610076411
      verified: true
    - name: Recall Macro
      type: recall
      value: 0.7617741060121812
      verified: true
    - name: Recall Micro
      type: recall
      value: 0.8322147651006712
      verified: true
    - name: Recall Weighted
      type: recall
      value: 0.8322147651006712
      verified: true
    - name: F1 Macro
      type: f1
      value: 0.7831814623565482
      verified: true
    - name: F1 Micro
      type: f1
      value: 0.8322147651006712
      verified: true
    - name: F1 Weighted
      type: f1
      value: 0.8226255909753084
      verified: true
    - name: loss
      type: loss
      value: 0.5406177043914795
      verified: true
---

<!-- 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. -->

# bert-base-uncased-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: 0.5406
- Matthews Correlation: 0.5880

## 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: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|
| No log        | 1.0   | 268  | 0.4598          | 0.5135               |
| 0.393         | 2.0   | 536  | 0.4875          | 0.5573               |
| 0.393         | 3.0   | 804  | 0.5406          | 0.5880               |


### Framework versions

- Transformers 4.20.0.dev0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1