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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilBERT_gptdata_with_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_gptdata_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: 0.2754
- Precision: 0.9537
- Recall: 0.9539
- F1: 0.9534
- Accuracy: 0.9533
## 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: 16
- eval_batch_size: 16
- 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 | 450 | 0.2320 | 0.9410 | 0.9412 | 0.9399 | 0.94 |
| 0.5426 | 2.0 | 900 | 0.2227 | 0.9465 | 0.9472 | 0.9460 | 0.9461 |
| 0.1125 | 3.0 | 1350 | 0.2242 | 0.9456 | 0.9446 | 0.9444 | 0.9439 |
| 0.0642 | 4.0 | 1800 | 0.2368 | 0.9557 | 0.9556 | 0.9550 | 0.955 |
| 0.0368 | 5.0 | 2250 | 0.2539 | 0.9515 | 0.9512 | 0.9513 | 0.9506 |
| 0.024 | 6.0 | 2700 | 0.2570 | 0.9543 | 0.9546 | 0.9539 | 0.9539 |
| 0.0106 | 7.0 | 3150 | 0.2576 | 0.9554 | 0.9547 | 0.9549 | 0.9544 |
| 0.0121 | 8.0 | 3600 | 0.2783 | 0.9538 | 0.9540 | 0.9534 | 0.9533 |
| 0.0047 | 9.0 | 4050 | 0.2817 | 0.9538 | 0.9540 | 0.9534 | 0.9533 |
| 0.003 | 10.0 | 4500 | 0.2754 | 0.9537 | 0.9539 | 0.9534 | 0.9533 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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