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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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