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--- |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: iab_classification-finetuned-mnli-finetuned-mnli |
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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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# iab_classification-finetuned-mnli-finetuned-mnli |
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This model was trained from scratch on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 4.5436 |
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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: 2 |
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- eval_batch_size: 2 |
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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: 50 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| No log | 1.0 | 15 | 5.0579 | |
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| No log | 2.0 | 30 | 2.5431 | |
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| No log | 3.0 | 45 | 3.2248 | |
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| No log | 4.0 | 60 | 3.9195 | |
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| No log | 5.0 | 75 | 4.2920 | |
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| No log | 6.0 | 90 | 4.4568 | |
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| No log | 7.0 | 105 | 4.5005 | |
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| No log | 8.0 | 120 | 4.8739 | |
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| No log | 9.0 | 135 | 4.4574 | |
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| No log | 10.0 | 150 | 4.5635 | |
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| No log | 11.0 | 165 | 4.3998 | |
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| No log | 12.0 | 180 | 4.3195 | |
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| No log | 13.0 | 195 | 3.8431 | |
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| No log | 14.0 | 210 | 4.2134 | |
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| No log | 15.0 | 225 | 4.2773 | |
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| No log | 16.0 | 240 | 4.0859 | |
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| No log | 17.0 | 255 | 3.7728 | |
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| No log | 18.0 | 270 | 3.6935 | |
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| No log | 19.0 | 285 | 4.0160 | |
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| No log | 20.0 | 300 | 4.3259 | |
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| No log | 21.0 | 315 | 4.3933 | |
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| No log | 22.0 | 330 | 4.4054 | |
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| No log | 23.0 | 345 | 4.3431 | |
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| No log | 24.0 | 360 | 4.3030 | |
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| No log | 25.0 | 375 | 4.3601 | |
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| No log | 26.0 | 390 | 4.3288 | |
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| No log | 27.0 | 405 | 4.2502 | |
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| No log | 28.0 | 420 | 4.1835 | |
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| No log | 29.0 | 435 | 4.2719 | |
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| No log | 30.0 | 450 | 4.2541 | |
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| No log | 31.0 | 465 | 4.2910 | |
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| No log | 32.0 | 480 | 4.3543 | |
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| No log | 33.0 | 495 | 4.4530 | |
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| 0.2652 | 34.0 | 510 | 4.3851 | |
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| 0.2652 | 35.0 | 525 | 4.3539 | |
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| 0.2652 | 36.0 | 540 | 4.4083 | |
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| 0.2652 | 37.0 | 555 | 4.3998 | |
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| 0.2652 | 38.0 | 570 | 4.4422 | |
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| 0.2652 | 39.0 | 585 | 4.4466 | |
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| 0.2652 | 40.0 | 600 | 4.4148 | |
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| 0.2652 | 41.0 | 615 | 4.4509 | |
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| 0.2652 | 42.0 | 630 | 4.4941 | |
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| 0.2652 | 43.0 | 645 | 4.5451 | |
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| 0.2652 | 44.0 | 660 | 4.5409 | |
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| 0.2652 | 45.0 | 675 | 4.5605 | |
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| 0.2652 | 46.0 | 690 | 4.5356 | |
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| 0.2652 | 47.0 | 705 | 4.5376 | |
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| 0.2652 | 48.0 | 720 | 4.5301 | |
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| 0.2652 | 49.0 | 735 | 4.5396 | |
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| 0.2652 | 50.0 | 750 | 4.5436 | |
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### Framework versions |
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- Transformers 4.22.1 |
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- Pytorch 1.10.0 |
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- Datasets 2.5.1 |
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- Tokenizers 0.12.1 |
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