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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: facility-classifier |
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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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# facility-classifier |
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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: 0.4422 |
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- Accuracy: 0.7872 |
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- F1: 0.7854 |
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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: 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: 6 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 0.671 | 1.0 | 12 | 0.6529 | 0.6596 | 0.6441 | |
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| 0.5845 | 2.0 | 24 | 0.5722 | 0.7447 | 0.7461 | |
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| 0.4902 | 3.0 | 36 | 0.5091 | 0.7447 | 0.7461 | |
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| 0.378 | 4.0 | 48 | 0.4797 | 0.7660 | 0.7670 | |
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| 0.354 | 5.0 | 60 | 0.4487 | 0.8085 | 0.8029 | |
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| 0.2865 | 6.0 | 72 | 0.4422 | 0.7872 | 0.7854 | |
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### Framework versions |
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- Transformers 4.18.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 2.1.0 |
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- Tokenizers 0.12.1 |
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