---
tags:
- generated_from_trainer
datasets:
- go_emotions
metrics:
- accuracy
- f1
model-index:
- name: goemotions_bertspanish_finetunig_f
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: go_emotions
      type: go_emotions
      config: simplified
      split: test
      args: simplified
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.44333333333333336
    - name: F1
      type: f1
      value: 0.3107562259034207
---

<!-- 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. -->

# goemotions_bertspanish_finetunig_f

This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-cased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased) on the go_emotions dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2528
- Accuracy: 0.4433
- F1: 0.3108

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7

### Training results



### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3