denizspynk
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update model card README.md
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README.md
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---
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- f1
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- recall
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model-index:
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- name: requirements_ambiguity_v2
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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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# requirements_ambiguity_v2
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This model is a fine-tuned version of [GroNLP/bert-base-dutch-cased](https://huggingface.co/GroNLP/bert-base-dutch-cased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8136
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- Accuracy: 0.8189
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- F1: 0.8189
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- Recall: 0.7604
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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: 64
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- eval_batch_size: 64
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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: 4
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|
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| 0.5247 | 1.0 | 32 | 0.4726 | 0.8110 | 0.8092 | 0.7083 |
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| 0.2684 | 2.0 | 64 | 0.5090 | 0.7874 | 0.7897 | 0.7917 |
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| 0.1319 | 3.0 | 96 | 0.7653 | 0.8031 | 0.8027 | 0.7292 |
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| 0.035 | 4.0 | 128 | 0.8136 | 0.8189 | 0.8189 | 0.7604 |
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### Framework versions
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- Transformers 4.24.0
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- Pytorch 2.0.0
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- Datasets 2.9.0
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- Tokenizers 0.11.0
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