---
tags:
- generated_from_trainer
datasets:
- go_emotions
metrics:
- accuracy
- f1
model-index:
- name: electricidad-base-finetuned-go_emotions-es-2
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: go_emotions
      type: go_emotions
      config: simplified
      split: train
      args: simplified
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.5591468777484608
    - name: F1
      type: f1
      value: 0.5581665299693344
---

<!-- 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-2

This model is a fine-tuned version of [mrm8488/electricidad-base-discriminator](https://huggingface.co/mrm8488/electricidad-base-discriminator) on the go_emotions dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0837
- Accuracy: 0.5591
- F1: 0.5582

## 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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 1.7525        | 1.0   | 2270  | 1.6088          | 0.5618   | 0.5076 |
| 1.4522        | 2.0   | 4540  | 1.4687          | 0.5807   | 0.5534 |
| 1.2798        | 3.0   | 6810  | 1.4550          | 0.5910   | 0.5773 |
| 1.0825        | 4.0   | 9080  | 1.5068          | 0.5873   | 0.5726 |
| 0.9214        | 5.0   | 11350 | 1.6168          | 0.5776   | 0.5743 |
| 0.7696        | 6.0   | 13620 | 1.7338          | 0.5776   | 0.5722 |
| 0.6688        | 7.0   | 15890 | 1.8733          | 0.5631   | 0.5596 |
| 0.553         | 8.0   | 18160 | 1.9571          | 0.5574   | 0.5591 |
| 0.4626        | 9.0   | 20430 | 2.0499          | 0.5646   | 0.5625 |
| 0.4399        | 10.0  | 22700 | 2.0837          | 0.5591   | 0.5582 |


### Framework versions

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