---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert-base-uncased-mrpc
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE MRPC
      type: glue
      args: mrpc
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8578431372549019
    - name: F1
      type: f1
      value: 0.9023569023569024
  - task:
      type: natural-language-inference
      name: Natural Language Inference
    dataset:
      name: glue
      type: glue
      config: mrpc
      split: validation
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8578431372549019
      verified: true
    - name: Precision
      type: precision
      value: 0.8507936507936508
      verified: true
    - name: Recall
      type: recall
      value: 0.9605734767025089
      verified: true
    - name: AUC
      type: auc
      value: 0.8931260592926008
      verified: true
    - name: F1
      type: f1
      value: 0.9023569023569024
      verified: true
    - name: loss
      type: loss
      value: 0.5572634935379028
      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-mrpc

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5572
- Accuracy: 0.8578
- F1: 0.9024
- Combined Score: 0.8801

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 5.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| No log        | 1.0   | 230  | 0.4111          | 0.8088   | 0.8704 | 0.8396         |
| No log        | 2.0   | 460  | 0.3762          | 0.8480   | 0.8942 | 0.8711         |
| 0.4287        | 3.0   | 690  | 0.5572          | 0.8578   | 0.9024 | 0.8801         |
| 0.4287        | 4.0   | 920  | 0.6087          | 0.8554   | 0.8977 | 0.8766         |
| 0.1172        | 5.0   | 1150 | 0.6524          | 0.8456   | 0.8901 | 0.8678         |


### Framework versions

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