---
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: 0.7065
- Precision: 0.8418
- Recall: 0.8521
- F1: 0.8453
- Accuracy: 0.8838

## 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  | 0.5948          | 0.7470    | 0.8351 | 0.7753 | 0.8375   |
| 0.8584        | 2.0   | 514  | 0.5402          | 0.7946    | 0.8405 | 0.8048 | 0.8643   |
| 0.8584        | 3.0   | 771  | 0.5362          | 0.8012    | 0.8425 | 0.8164 | 0.8682   |
| 0.3181        | 4.0   | 1028 | 0.5224          | 0.8062    | 0.8622 | 0.8290 | 0.875    |
| 0.3181        | 5.0   | 1285 | 0.5766          | 0.8234    | 0.8514 | 0.8353 | 0.8769   |
| 0.1767        | 6.0   | 1542 | 0.6231          | 0.8229    | 0.8531 | 0.8363 | 0.8755   |
| 0.1767        | 7.0   | 1799 | 0.6359          | 0.8370    | 0.8576 | 0.8456 | 0.8847   |
| 0.1231        | 8.0   | 2056 | 0.6849          | 0.8391    | 0.8538 | 0.8452 | 0.8823   |
| 0.1231        | 9.0   | 2313 | 0.6961          | 0.8453    | 0.8450 | 0.8431 | 0.8823   |
| 0.0862        | 10.0  | 2570 | 0.7065          | 0.8418    | 0.8521 | 0.8453 | 0.8838   |


### Framework versions

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