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: distilbert-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: 0.5496503496503496
+    - name: Recall
+      type: recall
+      value: 0.36422613531047265
+    - name: F1
+      type: f1
+      value: 0.4381270903010034
+    - name: Accuracy
+      type: accuracy
+      value: 0.9468667179618706
+---
+
+<!-- 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. -->
+
+# distilbert-base-multilingual-cased-WNUT-ner
+
+This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the wnut_17 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3516
+- Precision: 0.5497
+- Recall: 0.3642
+- F1: 0.4381
+- Accuracy: 0.9469
+
+## 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  | 0.2727          | 0.6626    | 0.2530 | 0.3662 | 0.9402   |
+| No log        | 2.0   | 426  | 0.2636          | 0.5895    | 0.2715 | 0.3718 | 0.9429   |
+| 0.1729        | 3.0   | 639  | 0.2933          | 0.5931    | 0.3040 | 0.4020 | 0.9447   |
+| 0.1729        | 4.0   | 852  | 0.2861          | 0.5437    | 0.3457 | 0.4227 | 0.9453   |
+| 0.0503        | 5.0   | 1065 | 0.3270          | 0.5627    | 0.3494 | 0.4311 | 0.9455   |
+| 0.0503        | 6.0   | 1278 | 0.3277          | 0.5451    | 0.3531 | 0.4286 | 0.9463   |
+| 0.0503        | 7.0   | 1491 | 0.3471          | 0.5828    | 0.3457 | 0.4340 | 0.9467   |
+| 0.0231        | 8.0   | 1704 | 0.3594          | 0.5801    | 0.3457 | 0.4332 | 0.9464   |
+| 0.0231        | 9.0   | 1917 | 0.3550          | 0.5567    | 0.3503 | 0.4300 | 0.9467   |
+| 0.0121        | 10.0  | 2130 | 0.3516          | 0.5497    | 0.3642 | 0.4381 | 0.9469   |
+
+
+### Framework versions
+
+- Transformers 4.26.0
+- Pytorch 1.13.1+cu117
+- Datasets 2.9.0
+- Tokenizers 0.13.2