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---
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
|