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iab_classification-finetuned-mnli-finetuned-mnli

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@@ -11,9 +11,9 @@ 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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@@ -42,58 +42,58 @@ The following hyperparameters were used during training:
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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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  # iab_classification-finetuned-mnli-finetuned-mnli
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+ This model is a fine-tuned version of [mfreihaut/iab_classification-finetuned-mnli-finetuned-mnli](https://huggingface.co/mfreihaut/iab_classification-finetuned-mnli-finetuned-mnli) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.8711
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  ## Model description
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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 | 250 | 1.5956 |
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+ | 0.9361 | 2.0 | 500 | 0.0409 |
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+ | 0.9361 | 3.0 | 750 | 2.9853 |
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+ | 0.7634 | 4.0 | 1000 | 0.1317 |
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+ | 0.7634 | 5.0 | 1250 | 0.4056 |
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+ | 0.611 | 6.0 | 1500 | 1.8038 |
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+ | 0.611 | 7.0 | 1750 | 0.6305 |
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+ | 0.5627 | 8.0 | 2000 | 0.6923 |
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+ | 0.5627 | 9.0 | 2250 | 3.7410 |
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+ | 0.9863 | 10.0 | 2500 | 2.1912 |
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+ | 0.9863 | 11.0 | 2750 | 1.5405 |
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+ | 1.0197 | 12.0 | 3000 | 1.9271 |
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+ | 1.0197 | 13.0 | 3250 | 1.1741 |
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+ | 0.5186 | 14.0 | 3500 | 1.1864 |
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+ | 0.5186 | 15.0 | 3750 | 0.7945 |
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+ | 0.4042 | 16.0 | 4000 | 1.0645 |
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+ | 0.4042 | 17.0 | 4250 | 1.8826 |
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+ | 0.3637 | 18.0 | 4500 | 0.3234 |
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+ | 0.3637 | 19.0 | 4750 | 0.2641 |
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+ | 0.3464 | 20.0 | 5000 | 0.8596 |
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+ | 0.3464 | 21.0 | 5250 | 0.5601 |
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+ | 0.2449 | 22.0 | 5500 | 0.4543 |
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+ | 0.2449 | 23.0 | 5750 | 1.1986 |
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+ | 0.2595 | 24.0 | 6000 | 0.3642 |
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+ | 0.2595 | 25.0 | 6250 | 1.3606 |
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+ | 0.298 | 26.0 | 6500 | 0.8154 |
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+ | 0.298 | 27.0 | 6750 | 1.1105 |
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+ | 0.1815 | 28.0 | 7000 | 0.7443 |
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+ | 0.1815 | 29.0 | 7250 | 0.2616 |
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+ | 0.165 | 30.0 | 7500 | 0.5318 |
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+ | 0.165 | 31.0 | 7750 | 0.7608 |
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+ | 0.1435 | 32.0 | 8000 | 0.9647 |
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+ | 0.1435 | 33.0 | 8250 | 1.3749 |
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+ | 0.1516 | 34.0 | 8500 | 0.7167 |
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+ | 0.1516 | 35.0 | 8750 | 0.5426 |
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+ | 0.1359 | 36.0 | 9000 | 0.7225 |
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+ | 0.1359 | 37.0 | 9250 | 0.5453 |
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+ | 0.1266 | 38.0 | 9500 | 0.4825 |
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+ | 0.1266 | 39.0 | 9750 | 0.7271 |
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+ | 0.1153 | 40.0 | 10000 | 0.9044 |
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+ | 0.1153 | 41.0 | 10250 | 1.0363 |
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+ | 0.1175 | 42.0 | 10500 | 0.7987 |
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+ | 0.1175 | 43.0 | 10750 | 0.7596 |
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+ | 0.1089 | 44.0 | 11000 | 0.8637 |
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+ | 0.1089 | 45.0 | 11250 | 0.8327 |
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+ | 0.1092 | 46.0 | 11500 | 0.7161 |
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+ | 0.1092 | 47.0 | 11750 | 0.7768 |
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+ | 0.1068 | 48.0 | 12000 | 0.9059 |
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+ | 0.1068 | 49.0 | 12250 | 0.8829 |
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+ | 0.1045 | 50.0 | 12500 | 0.8711 |
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  ### Framework versions