update model card README.md

README.md

@@ -0,0 +1,89 @@
+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- article500v4_wikigold_split
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: Article_500v4_NER_Model_3Epochs_UNAUGMENTED
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: article500v4_wikigold_split
+      type: article500v4_wikigold_split
+      args: default
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.6463647959183674
+    - name: Recall
+      type: recall
+      value: 0.6729747675962815
+    - name: F1
+      type: f1
+      value: 0.6594014313597917
+    - name: Accuracy
+      type: accuracy
+      value: 0.9314611096204871
+---
+
+<!-- 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. -->
+
+# Article_500v4_NER_Model_3Epochs_UNAUGMENTED
+
+This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the article500v4_wikigold_split dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2062
+- Precision: 0.6464
+- Recall: 0.6730
+- F1: 0.6594
+- Accuracy: 0.9315
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 58   | 0.3048          | 0.3090    | 0.2978 | 0.3033 | 0.8852   |
+| No log        | 2.0   | 116  | 0.2127          | 0.6096    | 0.6567 | 0.6323 | 0.9271   |
+| No log        | 3.0   | 174  | 0.2062          | 0.6464    | 0.6730 | 0.6594 | 0.9315   |
+
+
+### Framework versions
+
+- Transformers 4.17.0
+- Pytorch 1.11.0+cu113
+- Datasets 2.4.0
+- Tokenizers 0.11.6