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---
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license: apache-2.0
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base_model: distilbert-base-uncased
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: distilBERT_gptdata_with_preprocessing_grid_search
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# distilBERT_gptdata_with_preprocessing_grid_search
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3040
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- Precision: 0.9588
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- Recall: 0.9588
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- F1: 0.9585
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- Accuracy: 0.9583
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| No log | 1.0 | 450 | 0.2178 | 0.9434 | 0.9437 | 0.9426 | 0.9428 |
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| 0.3833 | 2.0 | 900 | 0.2535 | 0.9449 | 0.9435 | 0.9424 | 0.9422 |
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| 0.1094 | 3.0 | 1350 | 0.2235 | 0.9551 | 0.9551 | 0.9548 | 0.9544 |
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| 0.0692 | 4.0 | 1800 | 0.2818 | 0.9545 | 0.9540 | 0.9534 | 0.9533 |
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| 0.0299 | 5.0 | 2250 | 0.2676 | 0.9569 | 0.9559 | 0.9562 | 0.9556 |
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| 0.019 | 6.0 | 2700 | 0.2761 | 0.9586 | 0.9584 | 0.9580 | 0.9578 |
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| 0.0074 | 7.0 | 3150 | 0.2832 | 0.9589 | 0.9590 | 0.9587 | 0.9583 |
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| 0.0063 | 8.0 | 3600 | 0.3009 | 0.9585 | 0.9583 | 0.9579 | 0.9578 |
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| 0.0029 | 9.0 | 4050 | 0.2968 | 0.9610 | 0.9610 | 0.9607 | 0.9606 |
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| 0.0013 | 10.0 | 4500 | 0.3040 | 0.9588 | 0.9588 | 0.9585 | 0.9583 |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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