---
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: 0.8262
- Precision: 0.8491
- Recall: 0.8536
- F1: 0.8511
- Accuracy: 0.8837

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.8922        | 1.0   | 514  | 0.5350          | 0.7953    | 0.8363 | 0.8092 | 0.8628   |
| 0.4521        | 2.0   | 1028 | 0.5359          | 0.8214    | 0.8385 | 0.8282 | 0.8652   |
| 0.2928        | 3.0   | 1542 | 0.5876          | 0.8264    | 0.8504 | 0.8367 | 0.8798   |
| 0.2099        | 4.0   | 2056 | 0.6974          | 0.8288    | 0.8435 | 0.8351 | 0.8764   |
| 0.1531        | 5.0   | 2570 | 0.8245          | 0.8367    | 0.8125 | 0.8232 | 0.8710   |
| 0.1124        | 6.0   | 3084 | 0.7553          | 0.8349    | 0.8543 | 0.8435 | 0.8764   |
| 0.1045        | 7.0   | 3598 | 0.7912          | 0.8452    | 0.8538 | 0.8492 | 0.8822   |
| 0.0716        | 8.0   | 4112 | 0.7909          | 0.8422    | 0.8529 | 0.8471 | 0.8788   |
| 0.0746        | 9.0   | 4626 | 0.8364          | 0.8462    | 0.8458 | 0.8458 | 0.8779   |
| 0.0533        | 10.0  | 5140 | 0.8262          | 0.8491    | 0.8536 | 0.8511 | 0.8837   |


### Framework versions

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