---
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: 0.1986
- Precision: 0.9664
- Recall: 0.9668
- F1: 0.9665
- Accuracy: 0.9667

## 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   | 225  | 0.1748          | 0.9549    | 0.9514 | 0.9520 | 0.9528   |
| No log        | 2.0   | 450  | 0.1584          | 0.9567    | 0.9563 | 0.9562 | 0.9567   |
| 0.291         | 3.0   | 675  | 0.1553          | 0.9622    | 0.9627 | 0.9622 | 0.9622   |
| 0.291         | 4.0   | 900  | 0.1571          | 0.9647    | 0.9651 | 0.9646 | 0.965    |
| 0.0501        | 5.0   | 1125 | 0.1747          | 0.9667    | 0.9671 | 0.9666 | 0.9667   |
| 0.0501        | 6.0   | 1350 | 0.1887          | 0.9650    | 0.9658 | 0.9653 | 0.9656   |
| 0.0111        | 7.0   | 1575 | 0.1862          | 0.9668    | 0.9666 | 0.9665 | 0.9667   |
| 0.0111        | 8.0   | 1800 | 0.1985          | 0.9647    | 0.9649 | 0.9647 | 0.965    |
| 0.0044        | 9.0   | 2025 | 0.1954          | 0.9658    | 0.9662 | 0.9659 | 0.9661   |
| 0.0044        | 10.0  | 2250 | 0.1986          | 0.9664    | 0.9668 | 0.9665 | 0.9667   |


### Framework versions

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