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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: 0.2381
- Precision: 0.9596
- Recall: 0.9599
- F1: 0.9594
- Accuracy: 0.9594
## 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 | 225 | 0.2213 | 0.9434 | 0.9430 | 0.9419 | 0.9422 |
| No log | 2.0 | 450 | 0.1806 | 0.9512 | 0.9516 | 0.9508 | 0.9506 |
| 0.3512 | 3.0 | 675 | 0.1927 | 0.9515 | 0.9518 | 0.9512 | 0.9511 |
| 0.3512 | 4.0 | 900 | 0.2410 | 0.9490 | 0.9494 | 0.9490 | 0.9489 |
| 0.044 | 5.0 | 1125 | 0.2280 | 0.9554 | 0.9556 | 0.9550 | 0.955 |
| 0.044 | 6.0 | 1350 | 0.2199 | 0.9611 | 0.9609 | 0.9606 | 0.9606 |
| 0.0176 | 7.0 | 1575 | 0.2272 | 0.9562 | 0.9565 | 0.9560 | 0.9561 |
| 0.0176 | 8.0 | 1800 | 0.2321 | 0.9574 | 0.9576 | 0.9572 | 0.9572 |
| 0.0067 | 9.0 | 2025 | 0.2397 | 0.9590 | 0.9593 | 0.9588 | 0.9589 |
| 0.0067 | 10.0 | 2250 | 0.2381 | 0.9596 | 0.9599 | 0.9594 | 0.9594 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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