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# ComNumPNdistilBERT

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) a subset (8000 samples as training and 2000 samples as validation) of the [ComNum](https://huggingface.co/datasets/abbassix/ComNum) dataset.
We changed every single digit on a certain position in the numeral into a special character. For example '26753' becomes '3𐄇 5𐄈 7𐄉 6𐄊 2𐄋'.
Since the order of magnitude of numerals in the test set is 6, while that of numerals in training and evaluation sets are from 0 to 5, and the fine-tuned model has never seen special character for digits of the order of magnitude of 6 (e.g., '1𐄏', '6𐄏' or '9𐄏'), it cannot generalize well.

It achieves the following results on the evaluation set:
- Loss: 0.0458
- Accuracy: 0.9875

It achieves the following results on the test set:
- Loss: 3.0438
- Accuracy: 0.5909

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## 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-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2951        | 1.0   | 1000 | 0.1900          | 0.886    |
| 0.09          | 2.0   | 2000 | 0.0701          | 0.9835   |
| 0.0382        | 3.0   | 3000 | 0.0458          | 0.9875   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "ComNumPNdistilBERT", "results": []}]}
transformers tensorboard safetensors distilbert text-classification generated_from_trainer base_model:distilbert-base-uncased license:apache-2.0 autotrain_compatible endpoints_compatible region:us