---
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: 0.6943
- Precision: 0.8467
- Recall: 0.8562
- F1: 0.8509
- 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: 3e-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  | 0.5790          | 0.7659    | 0.8225 | 0.7875 | 0.8472   |
| 0.7473        | 2.0   | 514  | 0.5007          | 0.8115    | 0.8503 | 0.8264 | 0.8647   |
| 0.7473        | 3.0   | 771  | 0.4903          | 0.8007    | 0.8418 | 0.8174 | 0.8594   |
| 0.2608        | 4.0   | 1028 | 0.5370          | 0.8249    | 0.8491 | 0.8350 | 0.8657   |
| 0.2608        | 5.0   | 1285 | 0.6034          | 0.8424    | 0.8514 | 0.8455 | 0.8803   |
| 0.1543        | 6.0   | 1542 | 0.5988          | 0.8396    | 0.8565 | 0.8466 | 0.8788   |
| 0.1543        | 7.0   | 1799 | 0.6736          | 0.8486    | 0.8453 | 0.8458 | 0.8769   |
| 0.0981        | 8.0   | 2056 | 0.6476          | 0.8400    | 0.8605 | 0.8492 | 0.8788   |
| 0.0981        | 9.0   | 2313 | 0.6837          | 0.8443    | 0.8510 | 0.8469 | 0.8788   |
| 0.0713        | 10.0  | 2570 | 0.6943          | 0.8467    | 0.8562 | 0.8509 | 0.8793   |


### Framework versions

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