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-v4.001
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: caner
+      type: caner
+      config: default
+      split: train[-1%:]
+      args: default
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.8814432989690721
+    - name: Recall
+      type: recall
+      value: 0.8208
+    - name: F1
+      type: f1
+      value: 0.8500414250207124
+    - name: Accuracy
+      type: accuracy
+      value: 0.9327371695178849
+---
+
+<!-- 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-v4.001
+
+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: 0.4995
+- Precision: 0.8814
+- Recall: 0.8208
+- F1: 0.8500
+- Accuracy: 0.9327
+
+## 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.2518        | 1.0   | 4842  | 0.5403          | 0.8354    | 0.7712 | 0.8020 | 0.9178   |
+| 0.1364        | 2.0   | 9684  | 0.4746          | 0.8728    | 0.8016 | 0.8357 | 0.9287   |
+| 0.0915        | 3.0   | 14526 | 0.4995          | 0.8814    | 0.8208 | 0.8500 | 0.9327   |
+
+
+### Framework versions
+
+- Transformers 4.27.4
+- Pytorch 1.13.1+cu116
+- Datasets 2.11.0
+- Tokenizers 0.13.2