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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: robbert1010_lrate10b16 |
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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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# robbert1010_lrate10b16 |
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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: 0.6021 |
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- Precisions: 0.8323 |
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- Recall: 0.7951 |
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- F-measure: 0.8088 |
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- Accuracy: 0.9164 |
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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: 0.0001 |
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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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| 0.6104 | 1.0 | 236 | 0.4304 | 0.8532 | 0.6700 | 0.6852 | 0.8707 | |
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| 0.32 | 2.0 | 472 | 0.3520 | 0.7761 | 0.7551 | 0.7413 | 0.8916 | |
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| 0.1989 | 3.0 | 708 | 0.3686 | 0.7500 | 0.7591 | 0.7465 | 0.9010 | |
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| 0.1331 | 4.0 | 944 | 0.4045 | 0.8289 | 0.7666 | 0.7835 | 0.9090 | |
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| 0.0784 | 5.0 | 1180 | 0.4307 | 0.8052 | 0.7759 | 0.7890 | 0.9092 | |
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| 0.0682 | 6.0 | 1416 | 0.4696 | 0.8101 | 0.7658 | 0.7770 | 0.9059 | |
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| 0.04 | 7.0 | 1652 | 0.5078 | 0.8450 | 0.7642 | 0.7820 | 0.9096 | |
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| 0.0256 | 8.0 | 1888 | 0.5718 | 0.8007 | 0.7830 | 0.7906 | 0.9058 | |
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| 0.0219 | 9.0 | 2124 | 0.5508 | 0.8078 | 0.7987 | 0.8000 | 0.9093 | |
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| 0.0162 | 10.0 | 2360 | 0.5786 | 0.8256 | 0.7791 | 0.7946 | 0.9141 | |
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| 0.0117 | 11.0 | 2596 | 0.5979 | 0.8360 | 0.7912 | 0.8046 | 0.9168 | |
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| 0.011 | 12.0 | 2832 | 0.6021 | 0.8323 | 0.7951 | 0.8088 | 0.9164 | |
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| 0.0079 | 13.0 | 3068 | 0.6115 | 0.8337 | 0.7956 | 0.8088 | 0.9166 | |
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| 0.0064 | 14.0 | 3304 | 0.6100 | 0.8305 | 0.7932 | 0.8064 | 0.9164 | |
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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 0.14.1 |
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