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--- |
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license: mit |
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tags: |
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- generated_from_trainer |
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datasets: |
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- dutch_social |
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metrics: |
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- accuracy |
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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: robbert-twitter-sentiment |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: dutch_social |
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type: dutch_social |
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args: dutch_social |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.749 |
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- name: F1 |
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type: f1 |
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value: 0.7491844724992662 |
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- name: Precision |
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type: precision |
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value: 0.7493911755249737 |
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- name: Recall |
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type: recall |
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value: 0.749 |
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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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# robbert-twitter-sentiment |
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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 the dutch_social dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6818 |
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- Accuracy: 0.749 |
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- F1: 0.7492 |
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- Precision: 0.7494 |
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- Recall: 0.749 |
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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: 5e-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: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.7485 | 1.0 | 188 | 0.7670 | 0.692 | 0.6915 | 0.6920 | 0.692 | |
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| 0.5202 | 2.0 | 376 | 0.6818 | 0.749 | 0.7492 | 0.7494 | 0.749 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 1.11.0+cpu |
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- Datasets 2.0.0 |
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- Tokenizers 0.12.0 |
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