---
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
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# 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: 0.7575
- Precision: 0.8533
- Recall: 0.8477
- F1: 0.8486
- Accuracy: 0.8847

## 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  | 0.5635          | 0.7528    | 0.8373 | 0.7788 | 0.8439   |
| 0.7607        | 2.0   | 514  | 0.5324          | 0.8060    | 0.8314 | 0.8098 | 0.8648   |
| 0.7607        | 3.0   | 771  | 0.5216          | 0.8152    | 0.8475 | 0.8265 | 0.8765   |
| 0.2593        | 4.0   | 1028 | 0.5493          | 0.8179    | 0.8585 | 0.8348 | 0.8823   |
| 0.2593        | 5.0   | 1285 | 0.6226          | 0.8220    | 0.8419 | 0.8308 | 0.8794   |
| 0.1473        | 6.0   | 1542 | 0.6677          | 0.8429    | 0.8485 | 0.8442 | 0.8818   |
| 0.1473        | 7.0   | 1799 | 0.6611          | 0.8316    | 0.8481 | 0.8381 | 0.8823   |
| 0.096         | 8.0   | 2056 | 0.7404          | 0.8528    | 0.8448 | 0.8478 | 0.8857   |
| 0.096         | 9.0   | 2313 | 0.7401          | 0.8531    | 0.8476 | 0.8484 | 0.8862   |
| 0.0642        | 10.0  | 2570 | 0.7575          | 0.8533    | 0.8477 | 0.8486 | 0.8847   |


### Framework versions

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