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--- |
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license: mit |
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base_model: pdelobelle/robbert-v2-dutch-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- recall |
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- accuracy |
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model-index: |
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- name: robbert_seed36_1311 |
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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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# robbert_seed36_1311 |
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This model is a fine-tuned version of [pdelobelle/robbert-v2-dutch-base](https://huggingface.co/pdelobelle/robbert-v2-dutch-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3538 |
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- Precisions: 0.8351 |
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- Recall: 0.8079 |
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- F-measure: 0.8173 |
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- Accuracy: 0.9422 |
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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: 7.5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 36 |
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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: 14 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:| |
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| 0.4364 | 1.0 | 236 | 0.2547 | 0.8525 | 0.7285 | 0.7372 | 0.9231 | |
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| 0.2196 | 2.0 | 472 | 0.2772 | 0.8456 | 0.7521 | 0.7718 | 0.9291 | |
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| 0.1273 | 3.0 | 708 | 0.2681 | 0.8056 | 0.7798 | 0.7897 | 0.9315 | |
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| 0.0799 | 4.0 | 944 | 0.2971 | 0.8835 | 0.7898 | 0.8158 | 0.9393 | |
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| 0.0541 | 5.0 | 1180 | 0.3302 | 0.8515 | 0.7815 | 0.8016 | 0.9373 | |
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| 0.0358 | 6.0 | 1416 | 0.3291 | 0.8140 | 0.7901 | 0.7994 | 0.9385 | |
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| 0.0217 | 7.0 | 1652 | 0.3538 | 0.8351 | 0.8079 | 0.8173 | 0.9422 | |
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| 0.0145 | 8.0 | 1888 | 0.3622 | 0.8331 | 0.8000 | 0.8113 | 0.9431 | |
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| 0.0092 | 9.0 | 2124 | 0.3782 | 0.8190 | 0.8098 | 0.8116 | 0.9402 | |
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| 0.0091 | 10.0 | 2360 | 0.4023 | 0.8499 | 0.7967 | 0.8149 | 0.9422 | |
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| 0.0068 | 11.0 | 2596 | 0.3932 | 0.8293 | 0.8062 | 0.8154 | 0.9409 | |
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| 0.0053 | 12.0 | 2832 | 0.3894 | 0.8415 | 0.7942 | 0.8108 | 0.9412 | |
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| 0.0023 | 13.0 | 3068 | 0.3910 | 0.8379 | 0.7987 | 0.8127 | 0.9426 | |
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| 0.0035 | 14.0 | 3304 | 0.3919 | 0.8349 | 0.7990 | 0.8110 | 0.9422 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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