---
library_name: transformers
license: mit
base_model: SamLowe/roberta-base-go_emotions
tags:
- generated_from_trainer
datasets:
- sem_eval_2018_task_1
metrics:
- f1
- accuracy
- precision
- recall
model-index:
- name: roberta-finetuned-sem_eval-english
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: sem_eval_2018_task_1
      type: sem_eval_2018_task_1
      config: subtask5.english
      split: validation
      args: subtask5.english
    metrics:
    - name: F1
      type: f1
      value: 0.7211585665193913
    - name: Accuracy
      type: accuracy
      value: 0.29232505643340856
    - name: Precision
      type: precision
      value: 0.7679038159958181
    - name: Recall
      type: recall
      value: 0.6797778806108283
---

<!-- 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-finetuned-sem_eval-english

This model is a fine-tuned version of [SamLowe/roberta-base-go_emotions](https://huggingface.co/SamLowe/roberta-base-go_emotions) on the sem_eval_2018_task_1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2916
- F1: 0.7212
- Roc Auc: 0.8106
- Accuracy: 0.2923
- Precision: 0.7679
- Recall: 0.6798

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|:---------:|:------:|
| 0.2744        | 1.0   | 855  | 0.2948          | 0.7061 | 0.7988  | 0.2957   | 0.7668    | 0.6543 |
| 0.2593        | 2.0   | 1710 | 0.2917          | 0.7144 | 0.8033  | 0.2968   | 0.7781    | 0.6603 |
| 0.2315        | 3.0   | 2565 | 0.2916          | 0.7212 | 0.8106  | 0.2923   | 0.7679    | 0.6798 |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.6.0+cu124
- Datasets 3.4.0
- Tokenizers 0.21.0