update model card README.md

README.md

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+---
+language:
+- mn
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: xlm-roberta-base-ner-hrl-ner-finetuning
+  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-ner-hrl-ner-finetuning
+
+This model is a fine-tuned version of [Davlan/xlm-roberta-base-ner-hrl](https://huggingface.co/Davlan/xlm-roberta-base-ner-hrl) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1135
+- Precision: 0.9290
+- Recall: 0.9367
+- F1: 0.9328
+- Accuracy: 0.9801
+
+## 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: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.1534        | 1.0   | 477  | 0.0870          | 0.9001    | 0.9124 | 0.9062 | 0.9740   |
+| 0.077         | 2.0   | 954  | 0.0764          | 0.9187    | 0.9321 | 0.9253 | 0.9789   |
+| 0.0529        | 3.0   | 1431 | 0.0845          | 0.9178    | 0.9313 | 0.9245 | 0.9791   |
+| 0.0377        | 4.0   | 1908 | 0.0805          | 0.9200    | 0.9310 | 0.9255 | 0.9795   |
+| 0.0292        | 5.0   | 2385 | 0.0918          | 0.9278    | 0.9346 | 0.9312 | 0.9795   |
+| 0.0204        | 6.0   | 2862 | 0.1016          | 0.9222    | 0.9323 | 0.9273 | 0.9790   |
+| 0.0167        | 7.0   | 3339 | 0.1066          | 0.9271    | 0.9327 | 0.9299 | 0.9790   |
+| 0.0134        | 8.0   | 3816 | 0.1088          | 0.9253    | 0.9358 | 0.9305 | 0.9797   |
+| 0.0101        | 9.0   | 4293 | 0.1134          | 0.9289    | 0.9357 | 0.9323 | 0.9798   |
+| 0.0079        | 10.0  | 4770 | 0.1135          | 0.9290    | 0.9367 | 0.9328 | 0.9801   |
+
+
+### Framework versions
+
+- Transformers 4.28.1
+- Pytorch 2.0.0+cu118
+- Datasets 2.12.0
+- Tokenizers 0.13.3