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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: distilbert-base-uncased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: superhero-distilbert-predictor |
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results: [] |
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datasets: |
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- rlogh/superhero-texts |
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--- |
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# superhero-distilbert-predictor |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the superhero-texts dataset. |
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This model maps brief descriptions of popular superheroes to their respective comic book universes. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0161 |
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- Accuracy: 1.0 |
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- F1: 1.0 |
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- Precision: 1.0 |
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- Recall: 1.0 |
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## Intended uses & limitations |
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This model is strictly intended for educational use. Do not use this model to draw real world conclusions. |
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## Training and evaluation data |
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This model was trained on an augmented set of 1100 synthetically generated superhero descriptions and their respective universe label. |
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This model was validated against a set of 100 original, human curated descriptions. |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.4148 | 1.0 | 88 | 0.2780 | 0.9489 | 0.9299 | 0.9127 | 0.9489 | |
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| 0.0861 | 2.0 | 176 | 0.0616 | 0.9830 | 0.9771 | 0.9721 | 0.9830 | |
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| 0.0227 | 3.0 | 264 | 0.0174 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0118 | 4.0 | 352 | 0.0099 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0074 | 5.0 | 440 | 0.0088 | 1.0 | 1.0 | 1.0 | 1.0 | |
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### Framework versions |
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- Transformers 4.56.1 |
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- Pytorch 2.8.0+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.22.0 |
