---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- text-classification
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: platzi-distilbert-model-similaritytexts-JorgeEnciso
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: datasetX
      type: glue
      config: mrpc
      split: validation
      args: mrpc
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7083333333333334
    - name: F1
      type: f1
      value: 0.8125984251968503
---

<!-- 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. -->

# platzi-distilbert-model-similaritytexts-JorgeEnciso

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the datasetX dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5871
- Accuracy: 0.7083
- F1: 0.8126

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.6336        | 1.09  | 500  | 0.6239          | 0.6838   | 0.8122 |
| 0.6337        | 2.18  | 1000 | 0.6223          | 0.6912   | 0.8158 |
| 0.6076        | 3.27  | 1500 | 0.5871          | 0.7083   | 0.8126 |
| 0.5585        | 4.36  | 2000 | 0.6390          | 0.6887   | 0.7776 |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3