---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilBERT_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_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: 0.8637
- Precision: 0.8392
- Recall: 0.8339
- F1: 0.8360
- Accuracy: 0.8630

## 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: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.9492        | 1.0   | 510  | 0.5973          | 0.7572    | 0.8287 | 0.7836 | 0.8434   |
| 0.4661        | 2.0   | 1020 | 0.5080          | 0.8146    | 0.8535 | 0.8311 | 0.8567   |
| 0.2954        | 3.0   | 1530 | 0.6910          | 0.8283    | 0.8231 | 0.8245 | 0.8591   |
| 0.2263        | 4.0   | 2040 | 0.7367          | 0.8448    | 0.8293 | 0.8363 | 0.8635   |
| 0.1749        | 5.0   | 2550 | 0.7399          | 0.8402    | 0.8373 | 0.8383 | 0.8650   |
| 0.1273        | 6.0   | 3060 | 0.7759          | 0.8352    | 0.8414 | 0.8377 | 0.8689   |
| 0.1051        | 7.0   | 3570 | 0.8864          | 0.8375    | 0.8271 | 0.8308 | 0.8616   |
| 0.0877        | 8.0   | 4080 | 0.8407          | 0.8327    | 0.8360 | 0.8335 | 0.8625   |
| 0.0781        | 9.0   | 4590 | 0.8586          | 0.8345    | 0.8362 | 0.8345 | 0.8645   |
| 0.0627        | 10.0  | 5100 | 0.8637          | 0.8392    | 0.8339 | 0.8360 | 0.8630   |


### Framework versions

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