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Third full training run on complete dataset

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@@ -16,8 +16,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [yhavinga/ul2-large-dutch](https://huggingface.co/yhavinga/ul2-large-dutch) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 4.2516
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- - Top-5-accuracy: 3.5577
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  ## Model description
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@@ -36,75 +36,37 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.03
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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: 10
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Top-5-accuracy |
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- |:-------------:|:------:|:-----:|:---------------:|:--------------:|
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- | 7.6676 | 0.1729 | 200 | 5.1849 | 0.0 |
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- | 6.7322 | 0.3457 | 400 | 4.6030 | 0.0680 |
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- | 6.3351 | 0.5186 | 600 | 4.5872 | 0.0 |
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- | 6.1233 | 0.6914 | 800 | 4.5459 | 0.0453 |
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- | 6.0233 | 0.8643 | 1000 | 4.6328 | 0.0453 |
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- | 5.9119 | 1.0372 | 1200 | 4.6239 | 0.0 |
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- | 5.7683 | 1.2100 | 1400 | 4.5214 | 0.0680 |
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- | 5.8039 | 1.3829 | 1600 | 4.4935 | 0.0680 |
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- | 5.7866 | 1.5557 | 1800 | 4.4634 | 0.1586 |
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- | 5.6501 | 1.7286 | 2000 | 4.5163 | 0.1360 |
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- | 5.5949 | 1.9015 | 2200 | 4.4098 | 0.0906 |
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- | 5.5334 | 2.0743 | 2400 | 4.4172 | 0.0906 |
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- | 5.5175 | 2.2472 | 2600 | 4.4015 | 0.1586 |
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- | 5.5198 | 2.4201 | 2800 | 4.4079 | 0.1586 |
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- | 5.4601 | 2.5929 | 3000 | 4.4179 | 0.3172 |
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- | 5.5095 | 2.7658 | 3200 | 4.4219 | 0.3626 |
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- | 5.3924 | 2.9386 | 3400 | 4.3597 | 0.3399 |
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- | 5.4045 | 3.1115 | 3600 | 4.3392 | 0.6798 |
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- | 5.347 | 3.2844 | 3800 | 4.3186 | 0.5892 |
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- | 5.3494 | 3.4572 | 4000 | 4.3192 | 0.6798 |
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- | 5.3725 | 3.6301 | 4200 | 4.3734 | 0.3852 |
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- | 5.3407 | 3.8029 | 4400 | 4.3198 | 1.2690 |
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- | 5.3895 | 3.9758 | 4600 | 4.3233 | 0.7478 |
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- | 5.2923 | 4.1487 | 4800 | 4.3004 | 0.7931 |
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- | 5.3286 | 4.3215 | 5000 | 4.3195 | 1.2010 |
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- | 5.2082 | 4.4944 | 5200 | 4.3138 | 1.6089 |
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- | 5.2735 | 4.6672 | 5400 | 4.3083 | 1.9261 |
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- | 5.2474 | 4.8401 | 5600 | 4.2709 | 2.1754 |
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- | 5.2209 | 5.0130 | 5800 | 4.2812 | 2.2660 |
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- | 5.1823 | 5.1858 | 6000 | 4.2709 | 2.7646 |
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- | 5.2629 | 5.3587 | 6200 | 4.2837 | 2.2207 |
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- | 5.1891 | 5.5315 | 6400 | 4.3217 | 2.3114 |
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- | 5.2377 | 5.7044 | 6600 | 4.2810 | 2.6966 |
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- | 5.1904 | 5.8773 | 6800 | 4.3004 | 2.4247 |
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- | 5.1698 | 6.0501 | 7000 | 4.2687 | 2.6513 |
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- | 5.2109 | 6.2230 | 7200 | 4.2725 | 2.9912 |
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- | 5.2525 | 6.3959 | 7400 | 4.3036 | 2.8325 |
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- | 5.1317 | 6.5687 | 7600 | 4.2520 | 3.3311 |
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- | 5.1662 | 6.7416 | 7800 | 4.2796 | 2.6059 |
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- | 5.1612 | 6.9144 | 8000 | 4.2556 | 2.9005 |
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- | 5.223 | 7.0873 | 8200 | 4.2581 | 3.2857 |
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- | 5.1323 | 7.2602 | 8400 | 4.2629 | 3.3084 |
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- | 5.1419 | 7.4330 | 8600 | 4.2433 | 3.3764 |
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- | 5.1321 | 7.6059 | 8800 | 4.2467 | 3.4670 |
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- | 5.083 | 7.7787 | 9000 | 4.2507 | 3.4670 |
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- | 5.1572 | 7.9516 | 9200 | 4.2737 | 3.3764 |
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- | 5.1645 | 8.1245 | 9400 | 4.2425 | 3.5123 |
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- | 5.1241 | 8.2973 | 9600 | 4.2509 | 3.3990 |
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- | 5.2118 | 8.4702 | 9800 | 4.2655 | 3.3311 |
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- | 5.1387 | 8.6430 | 10000 | 4.2600 | 3.4670 |
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- | 5.1755 | 8.8159 | 10200 | 4.2686 | 3.3764 |
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- | 5.1629 | 8.9888 | 10400 | 4.2540 | 3.4897 |
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- | 5.1535 | 9.1616 | 10600 | 4.2442 | 3.6257 |
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- | 5.2023 | 9.3345 | 10800 | 4.2558 | 3.4897 |
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- | 5.087 | 9.5073 | 11000 | 4.2468 | 3.5803 |
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- | 5.0679 | 9.6802 | 11200 | 4.2485 | 3.5803 |
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- | 5.1546 | 9.8531 | 11400 | 4.2516 | 3.5577 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [yhavinga/ul2-large-dutch](https://huggingface.co/yhavinga/ul2-large-dutch) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 5.6126
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+ - Top-5-accuracy: 0.0
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.001
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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: 5
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Top-5-accuracy |
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+ |:-------------:|:------:|:----:|:---------------:|:--------------:|
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+ | 8.4166 | 0.2577 | 200 | 5.9848 | 0.0 |
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+ | 8.297 | 0.5155 | 400 | 5.9446 | 0.0 |
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+ | 8.0509 | 0.7732 | 600 | 5.8986 | 0.0 |
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+ | 8.1095 | 1.0309 | 800 | 5.8153 | 0.0 |
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+ | 7.9101 | 1.2887 | 1000 | 5.7811 | 0.0 |
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+ | 8.0255 | 1.5464 | 1200 | 5.7496 | 0.0 |
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+ | 8.0218 | 1.8041 | 1400 | 5.7238 | 0.0 |
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+ | 8.0497 | 2.0619 | 1600 | 5.7016 | 0.0 |
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+ | 8.1829 | 2.3196 | 1800 | 5.6813 | 0.0 |
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+ | 8.0591 | 2.5773 | 2000 | 5.6719 | 0.0 |
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+ | 8.0816 | 2.8351 | 2200 | 5.6573 | 0.0 |
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+ | 7.9825 | 3.0928 | 2400 | 5.6475 | 0.0 |
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+ | 8.1364 | 3.3505 | 2600 | 5.6383 | 0.0 |
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+ | 7.9707 | 3.6082 | 2800 | 5.6298 | 0.0 |
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+ | 7.9173 | 3.8660 | 3000 | 5.6232 | 0.0 |
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+ | 8.0502 | 4.1237 | 3200 | 5.6226 | 0.0 |
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+ | 8.1764 | 4.3814 | 3400 | 5.6163 | 0.0 |
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+ | 7.9046 | 4.6392 | 3600 | 5.6141 | 0.0 |
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+ | 7.7162 | 4.8969 | 3800 | 5.6126 | 0.0 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions