---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- f1
- accuracy
model-index:
- name: bart-base-finetuned-mrpc
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: glue
      type: glue
      config: mrpc
      split: validation
      args: mrpc
    metrics:
    - name: F1
      type: f1
      value: 0.90625
    - name: Accuracy
      type: accuracy
      value: 0.8676470588235294
---

<!-- 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. -->

# bart-base-finetuned-mrpc

This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3674
- F1: 0.9062
- Accuracy: 0.8676

## 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: 45
- 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 | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|
| No log        | 1.0   | 115  | 0.4762          | 0.8663 | 0.7966   |
| No log        | 2.0   | 230  | 0.3451          | 0.9019 | 0.8603   |
| No log        | 3.0   | 345  | 0.3229          | 0.9028 | 0.8627   |
| No log        | 4.0   | 460  | 0.3236          | 0.9014 | 0.8627   |
| 0.3737        | 5.0   | 575  | 0.3674          | 0.9062 | 0.8676   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3