transformers pytorch tensorboard safetensors electra text-classification generated_from_trainer dataset:go_emotions-es-mt model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- go_emotions-es-mt
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
widget:
- text: Me gusta mucho su forma de ser
- text: Es una persona muy extraña...
- text: El dolor es desesperante
- text: No me esperaba una evolución tan positiva
- text: ¡Dios mío, es enorme!
- text: ¡Agg! Está asqueroso.
model-index:
- name: electricidad-base-finetuned-go_emotions-es
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: go_emotions-es-mt
      type: go_emotions-es-mt
      config: simplified
      split: train
      args: simplified
    metrics:
    - type: accuracy
      value: 0.5934476693051891
      name: Accuracy
    - type: f1
      value: 0.5806237685841615
      name: F1
---

<!-- 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. -->

# electricidad-base-finetuned-go_emotions-es

This model is a fine-tuned version of [mrm8488/electricidad-base-discriminator](https://huggingface.co/mrm8488/electricidad-base-discriminator) on the [go_emotions-es-mt](https://huggingface.co/datasets/mrm8488/go_emotions-es-mt) dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5111
- Accuracy: 0.5934
- F1: 0.5806

## 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: 64
- 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     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 1.729         | 1.0   | 2270  | 1.5835          | 0.5578   | 0.5044 |
| 1.4432        | 2.0   | 4540  | 1.4529          | 0.5842   | 0.5538 |
| 1.2688        | 3.0   | 6810  | 1.4445          | 0.5945   | 0.5770 |
| 1.1017        | 4.0   | 9080  | 1.4804          | 0.5937   | 0.5781 |
| 0.9999        | 5.0   | 11350 | 1.5111          | 0.5934   | 0.5806 |


### Framework versions

- Transformers 4.21.2
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
