---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilBERT_gptdata_with_preprocessing_grid_search
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilBERT_gptdata_with_preprocessing_grid_search

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co./distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2221
- Precision: 0.9563
- Recall: 0.9566
- F1: 0.9562
- Accuracy: 0.9561

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 225  | 0.2531          | 0.9361    | 0.9359 | 0.9346 | 0.935    |
| No log        | 2.0   | 450  | 0.1835          | 0.9514    | 0.9520 | 0.9512 | 0.9511   |
| 0.4372        | 3.0   | 675  | 0.1798          | 0.9543    | 0.9546 | 0.9539 | 0.9539   |
| 0.4372        | 4.0   | 900  | 0.2059          | 0.9499    | 0.9500 | 0.9497 | 0.9494   |
| 0.0575        | 5.0   | 1125 | 0.2002          | 0.9563    | 0.9567 | 0.9561 | 0.9561   |
| 0.0575        | 6.0   | 1350 | 0.2019          | 0.9557    | 0.9552 | 0.9553 | 0.955    |
| 0.0231        | 7.0   | 1575 | 0.2152          | 0.9548    | 0.9550 | 0.9546 | 0.9544   |
| 0.0231        | 8.0   | 1800 | 0.2156          | 0.9554    | 0.9556 | 0.9554 | 0.955    |
| 0.0116        | 9.0   | 2025 | 0.2240          | 0.9559    | 0.9561 | 0.9557 | 0.9556   |
| 0.0116        | 10.0  | 2250 | 0.2221          | 0.9563    | 0.9566 | 0.9562 | 0.9561   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3