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-small-finetuned-xglue-ner-longer10
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: wnut_17
+      type: wnut_17
+      config: wnut_17
+      split: train
+      args: wnut_17
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.5436746987951807
+    - name: Recall
+      type: recall
+      value: 0.4318181818181818
+    - name: F1
+      type: f1
+      value: 0.48133333333333334
+    - name: Accuracy
+      type: accuracy
+      value: 0.9250487441220323
+---
+
+<!-- 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-small-finetuned-xglue-ner-longer10
+
+This model is a fine-tuned version of [muhtasham/bert-small-finetuned-xglue-ner-longer6](https://huggingface.co/muhtasham/bert-small-finetuned-xglue-ner-longer6) on the wnut_17 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4645
+- Precision: 0.5437
+- Recall: 0.4318
+- F1: 0.4813
+- Accuracy: 0.9250
+
+## 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: 4
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 425  | 0.4872          | 0.6164    | 0.3959 | 0.4822 | 0.9253   |
+| 0.0385        | 2.0   | 850  | 0.4528          | 0.5512    | 0.4246 | 0.4797 | 0.9256   |
+| 0.0317        | 3.0   | 1275 | 0.4638          | 0.5431    | 0.4294 | 0.4796 | 0.9246   |
+| 0.0308        | 4.0   | 1700 | 0.4645          | 0.5437    | 0.4318 | 0.4813 | 0.9250   |
+
+
+### Framework versions
+
+- Transformers 4.21.1
+- Pytorch 1.12.1+cu113
+- Datasets 2.4.0
+- Tokenizers 0.12.1