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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: robdataaugmentation1511 |
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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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# robdataaugmentation1511 |
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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: 0.4187 |
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- Precisions: 0.8503 |
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- Recall: 0.8197 |
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- F-measure: 0.8320 |
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- Accuracy: 0.9446 |
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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: 34 |
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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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| 0.4276 | 1.0 | 284 | 0.2688 | 0.8001 | 0.7195 | 0.7402 | 0.9200 | |
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| 0.1871 | 2.0 | 568 | 0.2595 | 0.8183 | 0.7803 | 0.7948 | 0.9308 | |
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| 0.0942 | 3.0 | 852 | 0.2800 | 0.8083 | 0.8047 | 0.8042 | 0.9366 | |
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| 0.0542 | 4.0 | 1136 | 0.2841 | 0.8228 | 0.8232 | 0.8212 | 0.9402 | |
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| 0.0365 | 5.0 | 1420 | 0.3355 | 0.8472 | 0.8056 | 0.8224 | 0.9393 | |
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| 0.0228 | 6.0 | 1704 | 0.3860 | 0.8501 | 0.8009 | 0.8211 | 0.9405 | |
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| 0.0141 | 7.0 | 1988 | 0.3997 | 0.8320 | 0.8175 | 0.8233 | 0.9409 | |
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| 0.0132 | 8.0 | 2272 | 0.4225 | 0.8478 | 0.8025 | 0.8164 | 0.9397 | |
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| 0.0077 | 9.0 | 2556 | 0.3890 | 0.8258 | 0.8410 | 0.8312 | 0.9429 | |
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| 0.006 | 10.0 | 2840 | 0.3954 | 0.8354 | 0.8150 | 0.8235 | 0.9402 | |
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| 0.0045 | 11.0 | 3124 | 0.4266 | 0.8441 | 0.8136 | 0.8246 | 0.9424 | |
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| 0.0037 | 12.0 | 3408 | 0.4171 | 0.8364 | 0.8174 | 0.8245 | 0.9426 | |
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| 0.0021 | 13.0 | 3692 | 0.4221 | 0.8461 | 0.8192 | 0.8294 | 0.9434 | |
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| 0.0018 | 14.0 | 3976 | 0.4187 | 0.8503 | 0.8197 | 0.8320 | 0.9446 | |
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### Framework versions |
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- Transformers 4.35.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.7 |
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- Tokenizers 0.14.1 |
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