---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilBERT_without_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_without_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: 0.7803
- Precision: 0.8448
- Recall: 0.8438
- F1: 0.8437
- Accuracy: 0.8783

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.0001        | 1.0   | 514  | 0.6163          | 0.7620    | 0.8133 | 0.7790 | 0.8394   |
| 0.4832        | 2.0   | 1028 | 0.5556          | 0.8131    | 0.8284 | 0.8166 | 0.8623   |
| 0.3307        | 3.0   | 1542 | 0.5381          | 0.8168    | 0.8425 | 0.8254 | 0.8691   |
| 0.2429        | 4.0   | 2056 | 0.6014          | 0.8289    | 0.8455 | 0.8353 | 0.8720   |
| 0.1849        | 5.0   | 2570 | 0.6600          | 0.8367    | 0.8408 | 0.8375 | 0.8740   |
| 0.1564        | 6.0   | 3084 | 0.6724          | 0.8219    | 0.8491 | 0.8333 | 0.8696   |
| 0.1316        | 7.0   | 3598 | 0.7511          | 0.8536    | 0.8481 | 0.8501 | 0.8808   |
| 0.1037        | 8.0   | 4112 | 0.7284          | 0.8438    | 0.8494 | 0.8461 | 0.8798   |
| 0.0946        | 9.0   | 4626 | 0.7584          | 0.8452    | 0.8470 | 0.8457 | 0.8798   |
| 0.0731        | 10.0  | 5140 | 0.7803          | 0.8448    | 0.8438 | 0.8437 | 0.8783   |


### Framework versions

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