---
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: 0.7297
- Precision: 0.8417
- Recall: 0.8510
- F1: 0.8460
- Accuracy: 0.8793

## 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  | 0.4958          | 0.7757    | 0.8526 | 0.8027 | 0.8526   |
| 0.6647        | 2.0   | 514  | 0.4756          | 0.8336    | 0.8480 | 0.8386 | 0.8701   |
| 0.6647        | 3.0   | 771  | 0.4823          | 0.8197    | 0.8588 | 0.8360 | 0.8730   |
| 0.2305        | 4.0   | 1028 | 0.5479          | 0.8314    | 0.8618 | 0.8439 | 0.8735   |
| 0.2305        | 5.0   | 1285 | 0.5832          | 0.8295    | 0.8542 | 0.8401 | 0.8779   |
| 0.1282        | 6.0   | 1542 | 0.5929          | 0.8251    | 0.8627 | 0.8404 | 0.8745   |
| 0.1282        | 7.0   | 1799 | 0.7066          | 0.8476    | 0.8496 | 0.8472 | 0.8774   |
| 0.0828        | 8.0   | 2056 | 0.6873          | 0.8392    | 0.8510 | 0.8448 | 0.8764   |
| 0.0828        | 9.0   | 2313 | 0.7189          | 0.8410    | 0.8524 | 0.8461 | 0.8788   |
| 0.0566        | 10.0  | 2570 | 0.7297          | 0.8417    | 0.8510 | 0.8460 | 0.8793   |


### Framework versions

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