End of training

README.md

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+---
+language:
+- mn
+license: apache-2.0
+base_model: bert-base-multilingual-cased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-multilingual-cased-ner-demo
+  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. -->
+
+# bert-multilingual-cased-ner-demo
+
+This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1471
+- Precision: 0.9148
+- Recall: 0.9229
+- F1: 0.9188
+- Accuracy: 0.9759
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.1743        | 1.0   | 477  | 0.0992          | 0.8649    | 0.8914 | 0.8780 | 0.9695   |
+| 0.0848        | 2.0   | 954  | 0.0900          | 0.8822    | 0.9010 | 0.8915 | 0.9719   |
+| 0.0557        | 3.0   | 1431 | 0.1110          | 0.8848    | 0.9001 | 0.8924 | 0.9699   |
+| 0.0411        | 4.0   | 1908 | 0.1061          | 0.8993    | 0.9140 | 0.9066 | 0.9744   |
+| 0.0298        | 5.0   | 2385 | 0.1130          | 0.8923    | 0.9147 | 0.9034 | 0.9732   |
+| 0.0207        | 6.0   | 2862 | 0.1197          | 0.9078    | 0.9176 | 0.9127 | 0.9756   |
+| 0.0144        | 7.0   | 3339 | 0.1372          | 0.9053    | 0.9180 | 0.9116 | 0.9742   |
+| 0.0088        | 8.0   | 3816 | 0.1401          | 0.9080    | 0.9195 | 0.9137 | 0.9746   |
+| 0.0066        | 9.0   | 4293 | 0.1442          | 0.9100    | 0.9216 | 0.9158 | 0.9753   |
+| 0.0054        | 10.0  | 4770 | 0.1471          | 0.9148    | 0.9229 | 0.9188 | 0.9759   |
+
+
+### Framework versions
+
+- Transformers 4.35.1
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1