---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: superhero-distilbert-predictor
  results: []
datasets:
- rlogh/superhero-texts
---

# superhero-distilbert-predictor

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the superhero-texts dataset.
This model maps brief descriptions of popular superheroes to their respective comic book universes. 

It achieves the following results on the evaluation set:
- Loss: 0.0161
- Accuracy: 1.0
- F1: 1.0
- Precision: 1.0
- Recall: 1.0

## Intended uses & limitations

This model is strictly intended for educational use. Do not use this model to draw real world conclusions.

## Training and evaluation data

This model was trained on an augmented set of 1100 synthetically generated superhero descriptions and their respective universe label.
This model was validated against a set of 100 original, human curated descriptions.

## 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_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.4148        | 1.0   | 88   | 0.2780          | 0.9489   | 0.9299 | 0.9127    | 0.9489 |
| 0.0861        | 2.0   | 176  | 0.0616          | 0.9830   | 0.9771 | 0.9721    | 0.9830 |
| 0.0227        | 3.0   | 264  | 0.0174          | 1.0      | 1.0    | 1.0       | 1.0    |
| 0.0118        | 4.0   | 352  | 0.0099          | 1.0      | 1.0    | 1.0       | 1.0    |
| 0.0074        | 5.0   | 440  | 0.0088          | 1.0      | 1.0    | 1.0       | 1.0    |


### Framework versions

- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0