metadata

base_model: pysentimiento/robertuito-emotion-analysis
tags:
  - generated_from_trainer
datasets:
  - emotion
metrics:
  - accuracy
  - f1
model-index:
  - name: robertuito-emotion-analysis-finetuned-emotion
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: emotion
          type: emotion
          config: split
          split: validation
          args: split
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8655
          - name: F1
            type: f1
            value: 0.8628554689630553

robertuito-emotion-analysis-finetuned-emotion

This model is a fine-tuned version of pysentimiento/robertuito-emotion-analysis on the emotion dataset. It achieves the following results on the evaluation set:

Loss: 0.3934
Accuracy: 0.8655
F1: 0.8629

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: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.9288	1.0	250	0.5332	0.812	0.7915
0.4393	2.0	500	0.3934	0.8655	0.8629

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1