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Second training rerun on complete dataset

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  1. README.md +22 -22
README.md CHANGED
@@ -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: 5.6126
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- - Top-5-accuracy: 0.0
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  ## Model description
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@@ -36,7 +36,7 @@ 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: 0.001
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
@@ -48,25 +48,25 @@ The following hyperparameters were used during training:
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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
 
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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: 4.5684
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+ - Top-5-accuracy: 0.1158
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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: 0.03
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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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  | Training Loss | Epoch | Step | Validation Loss | Top-5-accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:--------------:|
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+ | 7.7153 | 0.2577 | 200 | 5.3876 | 0.0 |
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+ | 6.8602 | 0.5155 | 400 | 4.8652 | 0.0 |
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+ | 6.3689 | 0.7732 | 600 | 4.6435 | 0.0 |
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+ | 6.2303 | 1.0309 | 800 | 4.6293 | 0.0579 |
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+ | 6.0898 | 1.2887 | 1000 | 4.6395 | 0.0289 |
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+ | 6.0367 | 1.5464 | 1200 | 4.5855 | 0.0289 |
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+ | 5.8512 | 1.8041 | 1400 | 4.5860 | 0.0579 |
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+ | 5.9489 | 2.0619 | 1600 | 4.5672 | 0.0868 |
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+ | 5.7601 | 2.3196 | 1800 | 4.5522 | 0.0579 |
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+ | 5.7379 | 2.5773 | 2000 | 4.5572 | 0.0868 |
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+ | 5.7397 | 2.8351 | 2200 | 4.5559 | 0.0579 |
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+ | 5.7488 | 3.0928 | 2400 | 4.5769 | 0.1447 |
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+ | 5.7581 | 3.3505 | 2600 | 4.5421 | 0.1158 |
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+ | 5.6448 | 3.6082 | 2800 | 4.5174 | 0.1447 |
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+ | 5.6551 | 3.8660 | 3000 | 4.5773 | 0.1158 |
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+ | 5.6971 | 4.1237 | 3200 | 4.5495 | 0.0868 |
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+ | 5.7085 | 4.3814 | 3400 | 4.5392 | 0.1447 |
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+ | 5.6689 | 4.6392 | 3600 | 4.5707 | 0.1158 |
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+ | 5.5422 | 4.8969 | 3800 | 4.5684 | 0.1158 |
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  ### Framework versions