---
license: apache-2.0
tags:
- text-classification
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: jrtec-distilroberta-base-mrpc-glue-omar-espejel
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: datasetX
      type: glue
      config: mrpc
      split: train
      args: mrpc
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8161764705882353
    - name: F1
      type: f1
      value: 0.8747913188647747
---

<!-- 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. -->

# jrtec-distilroberta-base-mrpc-glue-omar-espejel

This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the datasetX dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4901
- Accuracy: 0.8162
- F1: 0.8748

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.4845        | 1.09  | 500  | 0.4901          | 0.8162   | 0.8748 |
| 0.3706        | 2.18  | 1000 | 0.6421          | 0.8162   | 0.8691 |
| 0.2003        | 3.27  | 1500 | 0.9711          | 0.8162   | 0.8760 |
| 0.1281        | 4.36  | 2000 | 0.8224          | 0.8480   | 0.8893 |
| 0.0717        | 5.45  | 2500 | 1.1803          | 0.8113   | 0.8511 |
| 0.0344        | 6.54  | 3000 | 1.1759          | 0.8480   | 0.8935 |
| 0.0277        | 7.63  | 3500 | 1.2140          | 0.8456   | 0.8927 |
| 0.0212        | 8.71  | 4000 | 1.0895          | 0.8554   | 0.8974 |
| 0.0071        | 9.8   | 4500 | 1.1849          | 0.8554   | 0.8991 |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1