update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- conll2003
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-cased-ner-fcit499
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: conll2003
+      type: conll2003
+      config: conll2003
+      split: train
+      args: conll2003
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.9417409184372858
+    - name: Recall
+      type: recall
+      value: 0.950207468879668
+    - name: F1
+      type: f1
+      value: 0.9459552495697073
+    - name: Accuracy
+      type: accuracy
+      value: 0.9905416329830234
+---
+
+<!-- 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-cased-ner-fcit499
+
+This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the conll2003 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0404
+- Precision: 0.9417
+- Recall: 0.9502
+- F1: 0.9460
+- Accuracy: 0.9905
+
+## 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: 64
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 157  | 0.0578          | 0.8782    | 0.8976 | 0.8878 | 0.9825   |
+| No log        | 2.0   | 314  | 0.0425          | 0.9317    | 0.9343 | 0.9330 | 0.9885   |
+| No log        | 3.0   | 471  | 0.0391          | 0.9381    | 0.9433 | 0.9407 | 0.9897   |
+| 0.1097        | 4.0   | 628  | 0.0397          | 0.9377    | 0.9467 | 0.9422 | 0.9900   |
+| 0.1097        | 5.0   | 785  | 0.0404          | 0.9417    | 0.9502 | 0.9460 | 0.9905   |
+
+
+### Framework versions
+
+- Transformers 4.24.0
+- Pytorch 1.12.1+cu113
+- Datasets 2.6.1
+- Tokenizers 0.13.2