---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilBERT_mergeddata_with_preprocessing_grid_search
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilBERT_mergeddata_with_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: 0.1825
- Precision: 0.9668
- Recall: 0.9672
- F1: 0.9669
- Accuracy: 0.9672

## 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   | 225  | 0.1820          | 0.9527    | 0.9500 | 0.9506 | 0.9511   |
| No log        | 2.0   | 450  | 0.1582          | 0.9583    | 0.9584 | 0.9578 | 0.9583   |
| 0.3586        | 3.0   | 675  | 0.1369          | 0.9677    | 0.9678 | 0.9676 | 0.9678   |
| 0.3586        | 4.0   | 900  | 0.1371          | 0.9702    | 0.9706 | 0.9703 | 0.9706   |
| 0.0493        | 5.0   | 1125 | 0.1567          | 0.9686    | 0.9690 | 0.9687 | 0.9689   |
| 0.0493        | 6.0   | 1350 | 0.1622          | 0.9680    | 0.9685 | 0.9681 | 0.9683   |
| 0.0181        | 7.0   | 1575 | 0.1684          | 0.9640    | 0.9643 | 0.9640 | 0.9644   |
| 0.0181        | 8.0   | 1800 | 0.1717          | 0.9663    | 0.9666 | 0.9664 | 0.9667   |
| 0.0051        | 9.0   | 2025 | 0.1791          | 0.9674    | 0.9678 | 0.9675 | 0.9678   |
| 0.0051        | 10.0  | 2250 | 0.1825          | 0.9668    | 0.9672 | 0.9669 | 0.9672   |


### Framework versions

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