metadata

tags:
  - generated_from_trainer
datasets:
  - go_emotions-es-mt
metrics:
  - accuracy
  - f1
model-index:
  - name: electricidad-base-finetuned-go_emotions-es
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: go_emotions-es-mt
          type: go_emotions-es-mt
          config: simplified
          split: train
          args: simplified
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.5934476693051891
          - name: F1
            type: f1
            value: 0.5806237685841615
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.

electricidad-base-finetuned-go_emotions-es

This model is a fine-tuned version of mrm8488/electricidad-base-discriminator on the 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