---
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
should probably proofread and complete it, then remove this comment. -->

# 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: 0.2381
- Precision: 0.9596
- Recall: 0.9599
- F1: 0.9594
- Accuracy: 0.9594

## 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: 3e-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  | 0.2213          | 0.9434    | 0.9430 | 0.9419 | 0.9422   |
| No log        | 2.0   | 450  | 0.1806          | 0.9512    | 0.9516 | 0.9508 | 0.9506   |
| 0.3512        | 3.0   | 675  | 0.1927          | 0.9515    | 0.9518 | 0.9512 | 0.9511   |
| 0.3512        | 4.0   | 900  | 0.2410          | 0.9490    | 0.9494 | 0.9490 | 0.9489   |
| 0.044         | 5.0   | 1125 | 0.2280          | 0.9554    | 0.9556 | 0.9550 | 0.955    |
| 0.044         | 6.0   | 1350 | 0.2199          | 0.9611    | 0.9609 | 0.9606 | 0.9606   |
| 0.0176        | 7.0   | 1575 | 0.2272          | 0.9562    | 0.9565 | 0.9560 | 0.9561   |
| 0.0176        | 8.0   | 1800 | 0.2321          | 0.9574    | 0.9576 | 0.9572 | 0.9572   |
| 0.0067        | 9.0   | 2025 | 0.2397          | 0.9590    | 0.9593 | 0.9588 | 0.9589   |
| 0.0067        | 10.0  | 2250 | 0.2381          | 0.9596    | 0.9599 | 0.9594 | 0.9594   |


### Framework versions

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