---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- go_emotions
metrics:
- accuracy
- f1
model-index:
- name: roberta-large-bne-finetuned-go_emotions-es
  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: 0.5668425681618294
    - name: F1
      type: f1
      value: 0.5572049178848779
---

<!-- 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. -->

# roberta-large-bne-finetuned-go_emotions-es

This model is a fine-tuned version of [PlanTL-GOB-ES/roberta-large-bne](https://huggingface.co/PlanTL-GOB-ES/roberta-large-bne) on the go_emotions dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2457
- Accuracy: 0.5668
- F1: 0.5572

## 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: 4
- 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     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 1.5678        | 1.0   | 9077  | 1.5649          | 0.5671   | 0.5197 |
| 1.3898        | 2.0   | 18154 | 1.5005          | 0.5776   | 0.5492 |
| 0.915         | 3.0   | 27231 | 1.8045          | 0.5891   | 0.5692 |
| 0.5424        | 4.0   | 36308 | 2.8463          | 0.5646   | 0.5519 |
| 0.2018        | 5.0   | 45385 | 3.2457          | 0.5668   | 0.5572 |


### Framework versions

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