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--- |
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base_model: microsoft/mpnet-base |
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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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model-index: |
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- name: mpnet-base-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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# mpnet-base-airlines-news-multi-label |
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This model is a fine-tuned version of [microsoft/mpnet-base](https://huggingface.co/microsoft/mpnet-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2478 |
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- F1: 0.8938 |
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- Roc Auc: 0.6465 |
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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: 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: 40 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:| |
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| No log | 1.0 | 57 | 0.3726 | 0.8319 | 0.5 | |
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| No log | 2.0 | 114 | 0.3361 | 0.8319 | 0.5 | |
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| No log | 3.0 | 171 | 0.3303 | 0.8319 | 0.5 | |
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| No log | 4.0 | 228 | 0.3249 | 0.8319 | 0.5 | |
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| No log | 5.0 | 285 | 0.3188 | 0.8319 | 0.5 | |
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| No log | 6.0 | 342 | 0.3141 | 0.8319 | 0.5 | |
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| No log | 7.0 | 399 | 0.3089 | 0.8319 | 0.5 | |
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| No log | 8.0 | 456 | 0.3042 | 0.8319 | 0.5 | |
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| 0.3595 | 9.0 | 513 | 0.2997 | 0.8319 | 0.5 | |
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| 0.3595 | 10.0 | 570 | 0.2940 | 0.8319 | 0.5 | |
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| 0.3595 | 11.0 | 627 | 0.2898 | 0.8319 | 0.5 | |
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| 0.3595 | 12.0 | 684 | 0.2856 | 0.8463 | 0.5032 | |
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| 0.3595 | 13.0 | 741 | 0.2819 | 0.8593 | 0.5096 | |
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| 0.3595 | 14.0 | 798 | 0.2789 | 0.8600 | 0.5128 | |
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| 0.3595 | 15.0 | 855 | 0.2757 | 0.8701 | 0.5220 | |
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| 0.3595 | 16.0 | 912 | 0.2723 | 0.8733 | 0.5312 | |
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| 0.3595 | 17.0 | 969 | 0.2698 | 0.8733 | 0.5312 | |
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| 0.2983 | 18.0 | 1026 | 0.2670 | 0.8808 | 0.5629 | |
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| 0.2983 | 19.0 | 1083 | 0.2652 | 0.8814 | 0.5661 | |
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| 0.2983 | 20.0 | 1140 | 0.2630 | 0.8786 | 0.5744 | |
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| 0.2983 | 21.0 | 1197 | 0.2612 | 0.8807 | 0.5840 | |
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| 0.2983 | 22.0 | 1254 | 0.2596 | 0.8818 | 0.5900 | |
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| 0.2983 | 23.0 | 1311 | 0.2580 | 0.8841 | 0.6024 | |
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| 0.2983 | 24.0 | 1368 | 0.2562 | 0.8878 | 0.6153 | |
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| 0.2983 | 25.0 | 1425 | 0.2555 | 0.8851 | 0.6056 | |
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| 0.2983 | 26.0 | 1482 | 0.2544 | 0.8860 | 0.6088 | |
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| 0.2747 | 27.0 | 1539 | 0.2535 | 0.8868 | 0.6148 | |
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| 0.2747 | 28.0 | 1596 | 0.2527 | 0.8878 | 0.6153 | |
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| 0.2747 | 29.0 | 1653 | 0.2519 | 0.8869 | 0.6121 | |
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| 0.2747 | 30.0 | 1710 | 0.2512 | 0.8875 | 0.6180 | |
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| 0.2747 | 31.0 | 1767 | 0.2501 | 0.8900 | 0.6277 | |
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| 0.2747 | 32.0 | 1824 | 0.2495 | 0.8923 | 0.6401 | |
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| 0.2747 | 33.0 | 1881 | 0.2492 | 0.8907 | 0.6337 | |
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| 0.2747 | 34.0 | 1938 | 0.2488 | 0.8922 | 0.6401 | |
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| 0.2747 | 35.0 | 1995 | 0.2485 | 0.8915 | 0.6369 | |
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| 0.2633 | 36.0 | 2052 | 0.2480 | 0.8922 | 0.6401 | |
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| 0.2633 | 37.0 | 2109 | 0.2478 | 0.8938 | 0.6465 | |
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| 0.2633 | 38.0 | 2166 | 0.2477 | 0.8930 | 0.6433 | |
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| 0.2633 | 39.0 | 2223 | 0.2476 | 0.8938 | 0.6465 | |
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| 0.2633 | 40.0 | 2280 | 0.2476 | 0.8938 | 0.6465 | |
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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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