---
language:
- en
license: mit
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: camembert-base-mrpc
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE MRPC
      type: glue
      args: mrpc
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8504901960784313
    - name: F1
      type: f1
      value: 0.8927943760984183
  - task:
      type: natural-language-inference
      name: Natural Language Inference
    dataset:
      name: glue
      type: glue
      config: mrpc
      split: validation
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8504901960784313
      verified: true
    - name: Precision
      type: precision
      value: 0.8758620689655172
      verified: true
    - name: Recall
      type: recall
      value: 0.910394265232975
      verified: true
    - name: AUC
      type: auc
      value: 0.9029062821260871
      verified: true
    - name: F1
      type: f1
      value: 0.8927943760984183
      verified: true
    - name: loss
      type: loss
      value: 0.42868512868881226
      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. -->

# camembert-base-mrpc

This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4286
- Accuracy: 0.8505
- F1: 0.8928
- Combined Score: 0.8716

## 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
- num_epochs: 5.0

### Training results



### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu102
- Datasets 2.1.0
- Tokenizers 0.11.6