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--- |
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license: apache-2.0 |
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base_model: bert-base-uncased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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- accuracy |
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model-index: |
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- name: bert-base-uncased-airlines-news-multi-label |
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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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# bert-base-uncased-airlines-news-multi-label |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2807 |
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- F1: 0.7124 |
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- Roc Auc: 0.8100 |
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- Accuracy: 0.6766 |
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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: 7e-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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- lr_scheduler_warmup_steps: 150 |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:| |
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| No log | 1.0 | 118 | 0.2992 | 0.2412 | 0.5680 | 0.5234 | |
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| No log | 2.0 | 236 | 0.2628 | 0.5603 | 0.7177 | 0.6255 | |
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| No log | 3.0 | 354 | 0.2785 | 0.5691 | 0.7044 | 0.6426 | |
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| No log | 4.0 | 472 | 0.2674 | 0.6309 | 0.7619 | 0.6340 | |
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| 0.2379 | 5.0 | 590 | 0.2640 | 0.6535 | 0.7768 | 0.6340 | |
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| 0.2379 | 6.0 | 708 | 0.2929 | 0.6596 | 0.7683 | 0.6596 | |
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| 0.2379 | 7.0 | 826 | 0.2778 | 0.7059 | 0.8189 | 0.6681 | |
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| 0.2379 | 8.0 | 944 | 0.2807 | 0.7124 | 0.8100 | 0.6766 | |
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| 0.0507 | 9.0 | 1062 | 0.3381 | 0.6688 | 0.7921 | 0.6511 | |
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| 0.0507 | 10.0 | 1180 | 0.3160 | 0.6919 | 0.8259 | 0.6468 | |
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| 0.0507 | 11.0 | 1298 | 0.3206 | 0.7063 | 0.8045 | 0.6936 | |
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| 0.0507 | 12.0 | 1416 | 0.3273 | 0.6943 | 0.8060 | 0.6766 | |
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| 0.0115 | 13.0 | 1534 | 0.3408 | 0.6794 | 0.7986 | 0.6638 | |
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| 0.0115 | 14.0 | 1652 | 0.3488 | 0.6817 | 0.7971 | 0.6681 | |
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| 0.0115 | 15.0 | 1770 | 0.3469 | 0.6962 | 0.8085 | 0.6766 | |
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| 0.0115 | 16.0 | 1888 | 0.3517 | 0.6795 | 0.7966 | 0.6596 | |
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| 0.0045 | 17.0 | 2006 | 0.3537 | 0.6814 | 0.8011 | 0.6596 | |
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| 0.0045 | 18.0 | 2124 | 0.3566 | 0.6857 | 0.8021 | 0.6638 | |
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| 0.0045 | 19.0 | 2242 | 0.3587 | 0.6795 | 0.7966 | 0.6596 | |
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| 0.0045 | 20.0 | 2360 | 0.3596 | 0.6795 | 0.7966 | 0.6596 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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