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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: 0.2221 |
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- Precision: 0.9563 |
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- Recall: 0.9566 |
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- F1: 0.9562 |
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- Accuracy: 0.9561 |
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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: 2e-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 | 0.2531 | 0.9361 | 0.9359 | 0.9346 | 0.935 | |
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| No log | 2.0 | 450 | 0.1835 | 0.9514 | 0.9520 | 0.9512 | 0.9511 | |
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| 0.4372 | 3.0 | 675 | 0.1798 | 0.9543 | 0.9546 | 0.9539 | 0.9539 | |
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| 0.4372 | 4.0 | 900 | 0.2059 | 0.9499 | 0.9500 | 0.9497 | 0.9494 | |
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| 0.0575 | 5.0 | 1125 | 0.2002 | 0.9563 | 0.9567 | 0.9561 | 0.9561 | |
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| 0.0575 | 6.0 | 1350 | 0.2019 | 0.9557 | 0.9552 | 0.9553 | 0.955 | |
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| 0.0231 | 7.0 | 1575 | 0.2152 | 0.9548 | 0.9550 | 0.9546 | 0.9544 | |
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| 0.0231 | 8.0 | 1800 | 0.2156 | 0.9554 | 0.9556 | 0.9554 | 0.955 | |
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| 0.0116 | 9.0 | 2025 | 0.2240 | 0.9559 | 0.9561 | 0.9557 | 0.9556 | |
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| 0.0116 | 10.0 | 2250 | 0.2221 | 0.9563 | 0.9566 | 0.9562 | 0.9561 | |
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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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