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update model card README.md
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README.md
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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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model-index:
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- name: verdict-classifier
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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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# verdict-classifier
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1856
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- F1 Macro: 0.8148
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- F1 Misinformation: 0.9764
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- F1 Factual: 0.9375
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- F1 Other: 0.5306
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- Prec Macro: 0.8117
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- Prec Misinformation: 0.9775
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- Prec Factual: 0.9375
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- Prec Other: 0.52
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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: 2e-05
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 42
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 32
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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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- lr_scheduler_warmup_steps: 30066
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- num_epochs: 1000
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Misinformation | F1 Factual | F1 Other | Prec Macro | Prec Misinformation | Prec Factual | Prec Other |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:-----------------:|:----------:|:--------:|:----------:|:-------------------:|:------------:|:----------:|
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| 0.8707 | 1.0 | 3758 | 0.2414 | 0.7832 | 0.9639 | 0.7857 | 0.6 | 0.7950 | 0.9683 | 0.9167 | 0.5 |
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| 0.3918 | 2.0 | 7516 | 0.1856 | 0.8148 | 0.9764 | 0.9375 | 0.5306 | 0.8117 | 0.9775 | 0.9375 | 0.52 |
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| 0.1766 | 3.0 | 11274 | 0.1942 | 0.8394 | 0.9809 | 0.9538 | 0.5833 | 0.8349 | 0.9820 | 0.9394 | 0.5833 |
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| 0.1071 | 4.0 | 15032 | 0.2078 | 0.8676 | 0.9786 | 0.9841 | 0.64 | 0.8650 | 0.9797 | 1.0 | 0.6154 |
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### Framework versions
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- Transformers 4.11.3
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- Pytorch 1.9.0+cu102
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- Datasets 1.9.0
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- Tokenizers 0.10.2
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