---
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: 0.8909
- Precision: 0.8485
- Recall: 0.8467
- F1: 0.8467
- Accuracy: 0.8857

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.9219        | 1.0   | 514  | 0.5751          | 0.8031    | 0.8211 | 0.8091 | 0.8658   |
| 0.4593        | 2.0   | 1028 | 0.5435          | 0.8461    | 0.8372 | 0.8333 | 0.8789   |
| 0.2853        | 3.0   | 1542 | 0.6109          | 0.8362    | 0.8385 | 0.8347 | 0.8794   |
| 0.2159        | 4.0   | 2056 | 0.6320          | 0.8349    | 0.8681 | 0.8492 | 0.8847   |
| 0.1531        | 5.0   | 2570 | 0.6988          | 0.8564    | 0.8532 | 0.8536 | 0.8901   |
| 0.1223        | 6.0   | 3084 | 0.8081          | 0.8447    | 0.8476 | 0.8456 | 0.8833   |
| 0.1073        | 7.0   | 3598 | 0.7644          | 0.8366    | 0.8501 | 0.8425 | 0.8833   |
| 0.0958        | 8.0   | 4112 | 0.8606          | 0.8522    | 0.8468 | 0.8488 | 0.8847   |
| 0.0769        | 9.0   | 4626 | 0.8468          | 0.8475    | 0.8482 | 0.8472 | 0.8857   |
| 0.061         | 10.0  | 5140 | 0.8909          | 0.8485    | 0.8467 | 0.8467 | 0.8857   |


### Framework versions

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