---
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: 0.7927
- Precision: 0.8512
- Recall: 0.8478
- F1: 0.8484
- Accuracy: 0.8842

## 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: 5e-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   | 257  | 0.5177          | 0.7547    | 0.8422 | 0.7806 | 0.8444   |
| 0.6866        | 2.0   | 514  | 0.4727          | 0.8301    | 0.8543 | 0.8372 | 0.8794   |
| 0.6866        | 3.0   | 771  | 0.5257          | 0.8261    | 0.8508 | 0.8347 | 0.8779   |
| 0.2332        | 4.0   | 1028 | 0.5768          | 0.8254    | 0.8651 | 0.8423 | 0.8818   |
| 0.2332        | 5.0   | 1285 | 0.6244          | 0.8405    | 0.8529 | 0.8462 | 0.8852   |
| 0.1201        | 6.0   | 1542 | 0.7367          | 0.8520    | 0.8507 | 0.8505 | 0.8838   |
| 0.1201        | 7.0   | 1799 | 0.6644          | 0.8419    | 0.8607 | 0.8498 | 0.8833   |
| 0.0848        | 8.0   | 2056 | 0.7632          | 0.8522    | 0.8433 | 0.8465 | 0.8833   |
| 0.0848        | 9.0   | 2313 | 0.7510          | 0.8515    | 0.8569 | 0.8532 | 0.8867   |
| 0.0517        | 10.0  | 2570 | 0.7927          | 0.8512    | 0.8478 | 0.8484 | 0.8842   |


### Framework versions

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