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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: 0.2838 |
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- Precision: 0.9548 |
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- Recall: 0.9549 |
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- F1: 0.9545 |
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- Accuracy: 0.9544 |
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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: 32 |
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- eval_batch_size: 32 |
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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 | 225 | 0.2093 | 0.9466 | 0.9460 | 0.9448 | 0.945 | |
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| No log | 2.0 | 450 | 0.1837 | 0.9581 | 0.9578 | 0.9575 | 0.9572 | |
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| 0.289 | 3.0 | 675 | 0.2127 | 0.9540 | 0.9533 | 0.9527 | 0.9528 | |
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| 0.289 | 4.0 | 900 | 0.2200 | 0.9558 | 0.9560 | 0.9556 | 0.9556 | |
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| 0.0448 | 5.0 | 1125 | 0.2501 | 0.9565 | 0.9568 | 0.9562 | 0.9561 | |
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| 0.0448 | 6.0 | 1350 | 0.2577 | 0.9561 | 0.9559 | 0.9557 | 0.9556 | |
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| 0.0118 | 7.0 | 1575 | 0.2600 | 0.9559 | 0.9552 | 0.9554 | 0.955 | |
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| 0.0118 | 8.0 | 1800 | 0.2770 | 0.9555 | 0.9552 | 0.9552 | 0.955 | |
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| 0.0044 | 9.0 | 2025 | 0.2838 | 0.9548 | 0.9549 | 0.9545 | 0.9544 | |
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| 0.0044 | 10.0 | 2250 | 0.2838 | 0.9548 | 0.9549 | 0.9545 | 0.9544 | |
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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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