---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-base-go_emotions
  results: []
datasets:
- google-research-datasets/go_emotions
pipeline_tag: text-classification
---

<!-- 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-base-go_emotions

This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset.
It achieves the following results on the validation set:
- Loss: 0.1086
- Accuracy: 0.4561
- Roc Auc: 0.9064
- Micro Precision: 0.6063
- Micro Recall: 0.5340
- Micro F1: 0.5679
- Macro Precision: 0.5800
- Macro Recall: 0.4344
- Macro F1: 0.4649
- Weighted Precision: 0.5994
- Weighted Recall: 0.5340
- Weighted F1: 0.5591

## 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: 5e-06
- train_batch_size: 8
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Roc Auc | Micro Precision | Micro Recall | Micro F1 | Macro Precision | Macro Recall | Macro F1 | Weighted Precision | Weighted Recall | Weighted F1 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|:--------:|:------------------:|:---------------:|:-----------:|
| 0.1047        | 1.0   | 5427  | 0.0973          | 0.3616   | 0.8668  | 0.7390          | 0.3710       | 0.4940   | 0.3548          | 0.1954       | 0.2192   | 0.5670             | 0.3710          | 0.4098      |
| 0.09          | 2.0   | 10854 | 0.0876          | 0.4195   | 0.9037  | 0.7497          | 0.4276       | 0.5446   | 0.5715          | 0.2731       | 0.3243   | 0.6961             | 0.4276          | 0.4875      |
| 0.0821        | 3.0   | 16281 | 0.0850          | 0.4477   | 0.9137  | 0.7294          | 0.4627       | 0.5662   | 0.5692          | 0.3174       | 0.3799   | 0.6893             | 0.4627          | 0.5258      |
| 0.0774        | 4.0   | 21708 | 0.0851          | 0.4591   | 0.9178  | 0.6930          | 0.4876       | 0.5725   | 0.5768          | 0.3765       | 0.4273   | 0.6745             | 0.4876          | 0.5435      |
| 0.0736        | 5.0   | 27135 | 0.0856          | 0.4657   | 0.9208  | 0.6844          | 0.4989       | 0.5771   | 0.5741          | 0.3909       | 0.4448   | 0.6715             | 0.4989          | 0.5557      |
| 0.0714        | 6.0   | 32562 | 0.0866          | 0.4619   | 0.9171  | 0.6674          | 0.4991       | 0.5711   | 0.5593          | 0.3845       | 0.4386   | 0.6529             | 0.4991          | 0.5515      |
| 0.0673        | 7.0   | 37989 | 0.0883          | 0.4607   | 0.9209  | 0.6585          | 0.5038       | 0.5708   | 0.5197          | 0.4151       | 0.4522   | 0.6417             | 0.5038          | 0.5539      |
| 0.0604        | 8.0   | 43416 | 0.0902          | 0.4773   | 0.9171  | 0.6530          | 0.5252       | 0.5822   | 0.5623          | 0.4192       | 0.4629   | 0.6316             | 0.5252          | 0.5646      |
| 0.0593        | 9.0   | 48843 | 0.0926          | 0.4714   | 0.9165  | 0.6319          | 0.5263       | 0.5743   | 0.5850          | 0.4208       | 0.4612   | 0.6235             | 0.5263          | 0.5625      |
| 0.0557        | 10.0  | 54270 | 0.0959          | 0.4639   | 0.9155  | 0.6319          | 0.5229       | 0.5723   | 0.5710          | 0.4340       | 0.4705   | 0.6227             | 0.5229          | 0.5602      |
| 0.0512        | 11.0  | 59697 | 0.0985          | 0.4631   | 0.9147  | 0.6203          | 0.5266       | 0.5696   | 0.5656          | 0.4470       | 0.4754   | 0.6162             | 0.5266          | 0.5605      |
| 0.0478        | 12.0  | 65124 | 0.1013          | 0.4644   | 0.9116  | 0.6191          | 0.5279       | 0.5699   | 0.5588          | 0.4426       | 0.4776   | 0.6159             | 0.5279          | 0.5607      |
| 0.0449        | 13.0  | 70551 | 0.1036          | 0.4696   | 0.9080  | 0.6188          | 0.5354       | 0.5741   | 0.5594          | 0.4395       | 0.4729   | 0.6073             | 0.5354          | 0.5618      |
| 0.042         | 14.0  | 75978 | 0.1055          | 0.4700   | 0.9071  | 0.6131          | 0.5409       | 0.5747   | 0.5761          | 0.4399       | 0.4698   | 0.6013             | 0.5409          | 0.5638      |
| 0.0392        | 15.0  | 81405 | 0.1086          | 0.4561   | 0.9064  | 0.6063          | 0.5340       | 0.5679   | 0.5800          | 0.4344       | 0.4649   | 0.5994             | 0.5340          | 0.5591      |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.20.3