---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert-large-uncased-finetuned-mrpc
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: glue
      type: glue
      config: mrpc
      split: validation
      args: mrpc
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8578431372549019
    - name: F1
      type: f1
      value: 0.9006849315068494
---

<!-- 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-large-uncased-finetuned-mrpc

This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6016
- Accuracy: 0.8578
- F1: 0.9007

## 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: 32
- seed: 91
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 115  | 0.4435          | 0.8162   | 0.8777 |
| No log        | 2.0   | 230  | 0.3542          | 0.8407   | 0.8870 |
| No log        | 3.0   | 345  | 0.4246          | 0.8652   | 0.9063 |
| No log        | 4.0   | 460  | 0.5290          | 0.8578   | 0.9010 |
| 0.2887        | 5.0   | 575  | 0.6016          | 0.8578   | 0.9007 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.13.3