update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- caner
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-finetuned-ner-v2.1
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: caner
+      type: caner
+      config: default
+      split: train[5%:6%]
+      args: default
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.8599439775910365
+    - name: Recall
+      type: recall
+      value: 0.8611500701262272
+    - name: F1
+      type: f1
+      value: 0.8605466012613876
+    - name: Accuracy
+      type: accuracy
+      value: 0.948203842940685
+---
+
+<!-- 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-finetuned-ner-v2.1
+
+This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the caner dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3598
+- Precision: 0.8599
+- Recall: 0.8612
+- F1: 0.8605
+- Accuracy: 0.9482
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.2352        | 1.0   | 3228 | 0.3782          | 0.8478    | 0.8359 | 0.8418 | 0.9348   |
+| 0.1572        | 2.0   | 6456 | 0.3229          | 0.8696    | 0.8513 | 0.8604 | 0.9461   |
+| 0.0994        | 3.0   | 9684 | 0.3598          | 0.8599    | 0.8612 | 0.8605 | 0.9482   |
+
+
+### Framework versions
+
+- Transformers 4.26.0
+- Pytorch 1.13.1+cu116
+- Datasets 2.9.0
+- Tokenizers 0.13.2