update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- wnut_17
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-base-multilingual-cased-WNUT-ner
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: wnut_17
+      type: wnut_17
+      config: wnut_17
+      split: test
+      args: wnut_17
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.5913669064748202
+    - name: Recall
+      type: recall
+      value: 0.3809082483781279
+    - name: F1
+      type: f1
+      value: 0.463359639233371
+    - name: Accuracy
+      type: accuracy
+      value: 0.9500726682055228
+---
+
+<!-- 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-base-multilingual-cased-WNUT-ner
+
+This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the wnut_17 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3832
+- Precision: 0.5914
+- Recall: 0.3809
+- F1: 0.4634
+- Accuracy: 0.9501
+
+## 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: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 213  | 0.2791          | 0.6008    | 0.2817 | 0.3836 | 0.9427   |
+| No log        | 2.0   | 426  | 0.2697          | 0.6520    | 0.3299 | 0.4382 | 0.9479   |
+| 0.148         | 3.0   | 639  | 0.2846          | 0.5783    | 0.3661 | 0.4484 | 0.9492   |
+| 0.148         | 4.0   | 852  | 0.3032          | 0.6248    | 0.3642 | 0.4602 | 0.9500   |
+| 0.0413        | 5.0   | 1065 | 0.3355          | 0.5729    | 0.3568 | 0.4397 | 0.9495   |
+| 0.0413        | 6.0   | 1278 | 0.3343          | 0.5714    | 0.3892 | 0.4631 | 0.9501   |
+| 0.0413        | 7.0   | 1491 | 0.3522          | 0.5877    | 0.3818 | 0.4629 | 0.9500   |
+| 0.0182        | 8.0   | 1704 | 0.3844          | 0.6120    | 0.3698 | 0.4610 | 0.9499   |
+| 0.0182        | 9.0   | 1917 | 0.3847          | 0.5986    | 0.3828 | 0.4669 | 0.9504   |
+| 0.008         | 10.0  | 2130 | 0.3832          | 0.5914    | 0.3809 | 0.4634 | 0.9501   |
+
+
+### Framework versions
+
+- Transformers 4.26.0
+- Pytorch 1.13.1+cu117
+- Datasets 2.9.0
+- Tokenizers 0.13.2