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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: 0.2808
- Precision: 0.9608
- Recall: 0.9612
- F1: 0.9607
- Accuracy: 0.9606
## 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: 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 | 0.2169 | 0.9437 | 0.9445 | 0.9432 | 0.9433 |
| 0.4523 | 2.0 | 900 | 0.1979 | 0.9486 | 0.9486 | 0.9479 | 0.9478 |
| 0.109 | 3.0 | 1350 | 0.2404 | 0.9545 | 0.9539 | 0.9533 | 0.9533 |
| 0.0659 | 4.0 | 1800 | 0.2330 | 0.9559 | 0.9555 | 0.9550 | 0.955 |
| 0.0301 | 5.0 | 2250 | 0.2434 | 0.9580 | 0.9583 | 0.9580 | 0.9578 |
| 0.0201 | 6.0 | 2700 | 0.2462 | 0.9572 | 0.9569 | 0.9570 | 0.9567 |
| 0.0089 | 7.0 | 3150 | 0.2618 | 0.9581 | 0.9585 | 0.9581 | 0.9578 |
| 0.0074 | 8.0 | 3600 | 0.2717 | 0.9616 | 0.9618 | 0.9612 | 0.9611 |
| 0.0025 | 9.0 | 4050 | 0.2805 | 0.9597 | 0.9601 | 0.9596 | 0.9594 |
| 0.0014 | 10.0 | 4500 | 0.2808 | 0.9608 | 0.9612 | 0.9607 | 0.9606 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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