---
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: 0.1742
- Precision: 0.9650
- Recall: 0.9650
- F1: 0.9648
- Accuracy: 0.965

## 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   | 225  | 0.2068          | 0.9550    | 0.9536 | 0.9537 | 0.9544   |
| No log        | 2.0   | 450  | 0.1497          | 0.9583    | 0.9585 | 0.9582 | 0.9583   |
| 0.445         | 3.0   | 675  | 0.1408          | 0.9628    | 0.9631 | 0.9627 | 0.9628   |
| 0.445         | 4.0   | 900  | 0.1484          | 0.9630    | 0.9630 | 0.9626 | 0.9628   |
| 0.0585        | 5.0   | 1125 | 0.1487          | 0.9675    | 0.9680 | 0.9676 | 0.9678   |
| 0.0585        | 6.0   | 1350 | 0.1538          | 0.9665    | 0.9670 | 0.9665 | 0.9667   |
| 0.0242        | 7.0   | 1575 | 0.1666          | 0.9644    | 0.9645 | 0.9642 | 0.9644   |
| 0.0242        | 8.0   | 1800 | 0.1709          | 0.9672    | 0.9673 | 0.9671 | 0.9672   |
| 0.0111        | 9.0   | 2025 | 0.1707          | 0.9670    | 0.9672 | 0.9670 | 0.9672   |
| 0.0111        | 10.0  | 2250 | 0.1742          | 0.9650    | 0.9650 | 0.9648 | 0.965    |


### Framework versions

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