---
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: 0.7859
- Precision: 0.8423
- Recall: 0.8487
- F1: 0.8452
- Accuracy: 0.8769

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.908         | 1.0   | 514  | 0.5671          | 0.7815    | 0.8256 | 0.7960 | 0.8511   |
| 0.4351        | 2.0   | 1028 | 0.5301          | 0.8371    | 0.8439 | 0.8400 | 0.8715   |
| 0.2993        | 3.0   | 1542 | 0.5461          | 0.8250    | 0.8605 | 0.8401 | 0.8754   |
| 0.2186        | 4.0   | 2056 | 0.6724          | 0.8348    | 0.8517 | 0.8417 | 0.8745   |
| 0.168         | 5.0   | 2570 | 0.6923          | 0.8410    | 0.8441 | 0.8417 | 0.8754   |
| 0.1302        | 6.0   | 3084 | 0.6834          | 0.8301    | 0.8600 | 0.8432 | 0.8740   |
| 0.1094        | 7.0   | 3598 | 0.7413          | 0.8400    | 0.8515 | 0.8453 | 0.8774   |
| 0.0876        | 8.0   | 4112 | 0.7654          | 0.8383    | 0.8529 | 0.8452 | 0.8788   |
| 0.0833        | 9.0   | 4626 | 0.7748          | 0.8474    | 0.8530 | 0.8499 | 0.8798   |
| 0.0593        | 10.0  | 5140 | 0.7859          | 0.8423    | 0.8487 | 0.8452 | 0.8769   |


### Framework versions

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