---
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: 0.6731
- Precision: 0.8400
- Recall: 0.8427
- F1: 0.8407
- Accuracy: 0.8779

## 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: 2e-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  | 0.6542          | 0.7446    | 0.8052 | 0.7657 | 0.8350   |
| 0.8635        | 2.0   | 514  | 0.5548          | 0.7961    | 0.8277 | 0.8056 | 0.8540   |
| 0.8635        | 3.0   | 771  | 0.4839          | 0.7912    | 0.8427 | 0.8115 | 0.8589   |
| 0.3097        | 4.0   | 1028 | 0.5256          | 0.8148    | 0.8544 | 0.8315 | 0.8667   |
| 0.3097        | 5.0   | 1285 | 0.5657          | 0.8346    | 0.8494 | 0.8413 | 0.8764   |
| 0.1839        | 6.0   | 1542 | 0.6005          | 0.8208    | 0.8430 | 0.8304 | 0.8710   |
| 0.1839        | 7.0   | 1799 | 0.6580          | 0.8319    | 0.8349 | 0.8314 | 0.8706   |
| 0.1254        | 8.0   | 2056 | 0.6348          | 0.8342    | 0.8515 | 0.8423 | 0.8774   |
| 0.1254        | 9.0   | 2313 | 0.6601          | 0.8314    | 0.8394 | 0.8348 | 0.8745   |
| 0.0935        | 10.0  | 2570 | 0.6731          | 0.8400    | 0.8427 | 0.8407 | 0.8779   |


### Framework versions

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