update model card README.md

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: xlm-roberta-base-finetuned-pos
+  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. -->
+
+# xlm-roberta-base-finetuned-pos
+
+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: 0.0706
+- Precision: 0.9800
+- Recall: 0.9808
+- F1: 0.9804
+- Accuracy: 0.9821
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.1627        | 1.0   | 1583 | 0.1289          | 0.9599    | 0.9633 | 0.9616 | 0.9653   |
+| 0.1009        | 2.0   | 3166 | 0.0931          | 0.9680    | 0.9716 | 0.9698 | 0.9730   |
+| 0.0705        | 3.0   | 4749 | 0.0766          | 0.9758    | 0.9774 | 0.9766 | 0.9786   |
+| 0.0536        | 4.0   | 6332 | 0.0697          | 0.9787    | 0.9795 | 0.9791 | 0.9812   |
+| 0.0419        | 5.0   | 7915 | 0.0706          | 0.9800    | 0.9808 | 0.9804 | 0.9821   |
+
+
+### Framework versions
+
+- Transformers 4.27.3
+- Pytorch 1.13.1+cu116
+- Datasets 2.10.1
+- Tokenizers 0.13.2