---
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: 0.8740
- Precision: 0.8582
- Recall: 0.8441
- F1: 0.8491
- Accuracy: 0.8896

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.8195        | 1.0   | 514  | 0.5442          | 0.7965    | 0.8464 | 0.8071 | 0.8638   |
| 0.4249        | 2.0   | 1028 | 0.6446          | 0.8539    | 0.8236 | 0.8306 | 0.8769   |
| 0.3014        | 3.0   | 1542 | 0.6167          | 0.8484    | 0.8472 | 0.8463 | 0.8818   |
| 0.2268        | 4.0   | 2056 | 0.6262          | 0.8493    | 0.8594 | 0.8523 | 0.8896   |
| 0.1549        | 5.0   | 2570 | 0.6261          | 0.8443    | 0.8585 | 0.8501 | 0.8862   |
| 0.124         | 6.0   | 3084 | 0.8133          | 0.8566    | 0.8454 | 0.8503 | 0.8876   |
| 0.1057        | 7.0   | 3598 | 0.7241          | 0.8645    | 0.8596 | 0.8584 | 0.8925   |
| 0.0955        | 8.0   | 4112 | 0.8449          | 0.8532    | 0.8334 | 0.8421 | 0.8862   |
| 0.0744        | 9.0   | 4626 | 0.8140          | 0.8544    | 0.8536 | 0.8527 | 0.8901   |
| 0.0493        | 10.0  | 5140 | 0.8740          | 0.8582    | 0.8441 | 0.8491 | 0.8896   |


### Framework versions

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