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---
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
---
<!-- 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. -->
# robertuito-emotion-analysis-finetuned-emotion
This model is a fine-tuned version of [pysentimiento/robertuito-emotion-analysis](https://huggingface.co/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
|