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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: robbert0510_lrate9b16 |
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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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# robbert0510_lrate9b16 |
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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: 0.5895 |
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- Precisions: 0.8184 |
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- Recall: 0.7998 |
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- F-measure: 0.8078 |
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- Accuracy: 0.9148 |
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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: 8e-05 |
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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: 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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| 0.5957 | 1.0 | 236 | 0.4045 | 0.8529 | 0.6860 | 0.6940 | 0.8784 | |
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| 0.3024 | 2.0 | 472 | 0.3456 | 0.7564 | 0.7584 | 0.7471 | 0.8964 | |
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| 0.1843 | 3.0 | 708 | 0.3792 | 0.8188 | 0.7691 | 0.7741 | 0.9087 | |
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| 0.1163 | 4.0 | 944 | 0.4231 | 0.8317 | 0.7678 | 0.7878 | 0.9060 | |
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| 0.0753 | 5.0 | 1180 | 0.4595 | 0.8051 | 0.7846 | 0.7911 | 0.9070 | |
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| 0.0496 | 6.0 | 1416 | 0.4942 | 0.8188 | 0.7803 | 0.7960 | 0.9087 | |
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| 0.0321 | 7.0 | 1652 | 0.5121 | 0.7966 | 0.7927 | 0.7900 | 0.9103 | |
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| 0.0246 | 8.0 | 1888 | 0.5057 | 0.8155 | 0.7959 | 0.8030 | 0.9148 | |
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| 0.0156 | 9.0 | 2124 | 0.5445 | 0.8039 | 0.7924 | 0.7967 | 0.9109 | |
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| 0.0118 | 10.0 | 2360 | 0.5646 | 0.8151 | 0.7948 | 0.8032 | 0.9140 | |
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| 0.0083 | 11.0 | 2596 | 0.5911 | 0.8387 | 0.7872 | 0.8075 | 0.9138 | |
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| 0.0052 | 12.0 | 2832 | 0.5895 | 0.8184 | 0.7998 | 0.8078 | 0.9148 | |
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| 0.0038 | 13.0 | 3068 | 0.5839 | 0.8193 | 0.7987 | 0.8078 | 0.9149 | |
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| 0.0026 | 14.0 | 3304 | 0.5911 | 0.8195 | 0.7926 | 0.8041 | 0.9135 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.0 |
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