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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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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: robbert2809_lrate7.5 |
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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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# robbert2809_lrate7.5 |
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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: 0.3477 |
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- Precision: 0.7368 |
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- Recall: 0.7716 |
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- F1: 0.7538 |
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- Accuracy: 0.9017 |
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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: 32 |
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- eval_batch_size: 32 |
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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: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 118 | 0.3855 | 0.6721 | 0.6533 | 0.6625 | 0.8795 | |
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| No log | 2.0 | 236 | 0.3511 | 0.6921 | 0.7284 | 0.7098 | 0.8880 | |
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| No log | 3.0 | 354 | 0.3477 | 0.7368 | 0.7716 | 0.7538 | 0.9017 | |
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| No log | 4.0 | 472 | 0.4055 | 0.7489 | 0.7628 | 0.7558 | 0.9019 | |
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| 0.3159 | 5.0 | 590 | 0.3930 | 0.7506 | 0.7488 | 0.7497 | 0.9035 | |
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| 0.3159 | 6.0 | 708 | 0.4131 | 0.7684 | 0.7716 | 0.7700 | 0.9082 | |
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| 0.3159 | 7.0 | 826 | 0.4382 | 0.7714 | 0.7786 | 0.7749 | 0.9093 | |
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| 0.3159 | 8.0 | 944 | 0.4478 | 0.7817 | 0.7698 | 0.7757 | 0.9097 | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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