update model card README.md

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: detect-femicide-news-xlmr
+  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. -->
+
+# detect-femicide-news-xlmr
+
+This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0161
+- Accuracy: 0.9973
+- Precision Neg: 0.9975
+- Precision Pos: 0.9967
+- Recall Neg: 0.9988
+- Recall Pos: 0.9933
+- F1 Score Neg: 0.9981
+- F1 Score Pos: 0.9950
+
+## 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: 1e-05
+- train_batch_size: 128
+- eval_batch_size: 8
+- seed: 1996
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 6
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision Neg | Precision Pos | Recall Neg | Recall Pos | F1 Score Neg | F1 Score Pos |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:-------------:|:----------:|:----------:|:------------:|:------------:|
+| 0.2758        | 1.0   | 204  | 0.1001          | 0.9718   | 0.9741        | 0.9654        | 0.9875     | 0.93       | 0.9808       | 0.9474       |
+| 0.0782        | 2.0   | 408  | 0.0505          | 0.9809   | 0.9839        | 0.9729        | 0.99       | 0.9567     | 0.9869       | 0.9647       |
+| 0.0501        | 3.0   | 612  | 0.0272          | 0.9927   | 0.9962        | 0.9834        | 0.9938     | 0.99       | 0.9950       | 0.9867       |
+| 0.0389        | 4.0   | 816  | 0.0201          | 0.9945   | 0.9938        | 0.9966        | 0.9988     | 0.9833     | 0.9963       | 0.9899       |
+| 0.031         | 5.0   | 1020 | 0.0175          | 0.9964   | 0.9963        | 0.9966        | 0.9988     | 0.99       | 0.9975       | 0.9933       |
+| 0.0235        | 6.0   | 1224 | 0.0161          | 0.9973   | 0.9975        | 0.9967        | 0.9988     | 0.9933     | 0.9981       | 0.9950       |
+
+
+### Framework versions
+
+- Transformers 4.16.2
+- Pytorch 1.10.2+cu113
+- Datasets 1.18.3
+- Tokenizers 0.11.0