update model card README.md

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+model-index:
+- name: verdict-classifier
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# verdict-classifier
+
+This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1856
+- F1 Macro: 0.8148
+- F1 Misinformation: 0.9764
+- F1 Factual: 0.9375
+- F1 Other: 0.5306
+- Prec Macro: 0.8117
+- Prec Misinformation: 0.9775
+- Prec Factual: 0.9375
+- Prec Other: 0.52
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 30066
+- num_epochs: 1000
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | F1 Macro | F1 Misinformation | F1 Factual | F1 Other | Prec Macro | Prec Misinformation | Prec Factual | Prec Other |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:-----------------:|:----------:|:--------:|:----------:|:-------------------:|:------------:|:----------:|
+| 0.8707        | 1.0   | 3758  | 0.2414          | 0.7832   | 0.9639            | 0.7857     | 0.6      | 0.7950     | 0.9683              | 0.9167       | 0.5        |
+| 0.3918        | 2.0   | 7516  | 0.1856          | 0.8148   | 0.9764            | 0.9375     | 0.5306   | 0.8117     | 0.9775              | 0.9375       | 0.52       |
+| 0.1766        | 3.0   | 11274 | 0.1942          | 0.8394   | 0.9809            | 0.9538     | 0.5833   | 0.8349     | 0.9820              | 0.9394       | 0.5833     |
+| 0.1071        | 4.0   | 15032 | 0.2078          | 0.8676   | 0.9786            | 0.9841     | 0.64     | 0.8650     | 0.9797              | 1.0          | 0.6154     |
+
+
+### Framework versions
+
+- Transformers 4.11.3
+- Pytorch 1.9.0+cu102
+- Datasets 1.9.0
+- Tokenizers 0.10.2