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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: 0.2808 |
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- Precision: 0.9608 |
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- Recall: 0.9612 |
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- F1: 0.9607 |
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- Accuracy: 0.9606 |
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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: 3e-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 | 0.2169 | 0.9437 | 0.9445 | 0.9432 | 0.9433 | |
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| 0.4523 | 2.0 | 900 | 0.1979 | 0.9486 | 0.9486 | 0.9479 | 0.9478 | |
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| 0.109 | 3.0 | 1350 | 0.2404 | 0.9545 | 0.9539 | 0.9533 | 0.9533 | |
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| 0.0659 | 4.0 | 1800 | 0.2330 | 0.9559 | 0.9555 | 0.9550 | 0.955 | |
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| 0.0301 | 5.0 | 2250 | 0.2434 | 0.9580 | 0.9583 | 0.9580 | 0.9578 | |
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| 0.0201 | 6.0 | 2700 | 0.2462 | 0.9572 | 0.9569 | 0.9570 | 0.9567 | |
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| 0.0089 | 7.0 | 3150 | 0.2618 | 0.9581 | 0.9585 | 0.9581 | 0.9578 | |
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| 0.0074 | 8.0 | 3600 | 0.2717 | 0.9616 | 0.9618 | 0.9612 | 0.9611 | |
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| 0.0025 | 9.0 | 4050 | 0.2805 | 0.9597 | 0.9601 | 0.9596 | 0.9594 | |
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| 0.0014 | 10.0 | 4500 | 0.2808 | 0.9608 | 0.9612 | 0.9607 | 0.9606 | |
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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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