---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: Distilbert-uncased
  results: []
---

<!-- 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. -->

# Distilbert-uncased-AS

Este es un modelo de finetuning  de  [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) sobre un dataset propios de tweets.
Se logra una error cuadrático bajo lo cual quiere decir que los valores predichos son muy cercanos a los observables o gold.
- Loss: 0.3510
- Rmse: 0.2543

## 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: 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rmse   |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.2091        | 1.0   | 642  | 0.1933          | 0.3052 |
| 0.1334        | 2.0   | 1284 | 0.1909          | 0.2481 |
| 0.0684        | 3.0   | 1926 | 0.2617          | 0.2466 |
| 0.0355        | 4.0   | 2568 | 0.3113          | 0.2513 |
| 0.0116        | 5.0   | 3210 | 0.3510          | 0.2543 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.0.1+cu117
- Datasets 2.18.0
- Tokenizers 0.19.1