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---
tags:
- generated_from_trainer
datasets:
- go_emotions
metrics:
- accuracy
- f1
model-index:
- name: electricidad-base-finetuned-go_emotions-es-2
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: 0.5591468777484608
- name: F1
type: f1
value: 0.5581665299693344
---
<!-- 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. -->
# electricidad-base-finetuned-go_emotions-es-2
This model is a fine-tuned version of [mrm8488/electricidad-base-discriminator](https://huggingface.co/mrm8488/electricidad-base-discriminator) on the go_emotions dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0837
- Accuracy: 0.5591
- F1: 0.5582
## 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 1.7525 | 1.0 | 2270 | 1.6088 | 0.5618 | 0.5076 |
| 1.4522 | 2.0 | 4540 | 1.4687 | 0.5807 | 0.5534 |
| 1.2798 | 3.0 | 6810 | 1.4550 | 0.5910 | 0.5773 |
| 1.0825 | 4.0 | 9080 | 1.5068 | 0.5873 | 0.5726 |
| 0.9214 | 5.0 | 11350 | 1.6168 | 0.5776 | 0.5743 |
| 0.7696 | 6.0 | 13620 | 1.7338 | 0.5776 | 0.5722 |
| 0.6688 | 7.0 | 15890 | 1.8733 | 0.5631 | 0.5596 |
| 0.553 | 8.0 | 18160 | 1.9571 | 0.5574 | 0.5591 |
| 0.4626 | 9.0 | 20430 | 2.0499 | 0.5646 | 0.5625 |
| 0.4399 | 10.0 | 22700 | 2.0837 | 0.5591 | 0.5582 |
### Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
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