update model card README.md

README.md

@@ -7,11 +7,9 @@ metrics:
 - recall
 - f1
 - accuracy
-widget:
-- text: |
-    [BEGIN_DOC]รายงานการจ่าาย[END_LINE]
-    1. แผนงานพัฒนาสภาวะสิ่งแวดล้อม 1,457,874,400 บาท[END_LINE]
-    2. การเดินทาง 333,324 บาท[END_LINE]
+model-index:
+- name: bkk-ner-model
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -21,11 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [Geotrend/bert-base-th-cased](https://huggingface.co/Geotrend/bert-base-th-cased) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0296
-- Precision: 0.8841
-- Recall: 0.9385
-- F1: 0.9104
-- Accuracy: 0.9891
+- Loss: 0.0518
+- Precision: 0.8850
+- Recall: 0.9615
+- F1: 0.9217
+- Accuracy: 0.9822
 
 ## Model description
 
@@ -50,22 +48,27 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 10
+- num_epochs: 15
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 8    | 0.3765          | 0.5616    | 0.8769 | 0.6847 | 0.8629   |
-| No log        | 2.0   | 16   | 0.1733          | 0.7152    | 0.9077 | 0.8    | 0.9554   |
-| No log        | 3.0   | 24   | 0.1046          | 0.7785    | 0.9462 | 0.8542 | 0.9664   |
-| No log        | 4.0   | 32   | 0.0665          | 0.8276    | 0.9231 | 0.8727 | 0.9756   |
-| No log        | 5.0   | 40   | 0.0566          | 0.8531    | 0.9385 | 0.8938 | 0.9790   |
-| No log        | 6.0   | 48   | 0.0458          | 0.8531    | 0.9385 | 0.8938 | 0.9815   |
-| No log        | 7.0   | 56   | 0.0327          | 0.8777    | 0.9385 | 0.9071 | 0.9882   |
-| No log        | 8.0   | 64   | 0.0366          | 0.8592    | 0.9385 | 0.8971 | 0.9832   |
-| No log        | 9.0   | 72   | 0.0295          | 0.8841    | 0.9385 | 0.9104 | 0.9891   |
-| No log        | 10.0  | 80   | 0.0296          | 0.8841    | 0.9385 | 0.9104 | 0.9891   |
+| No log        | 1.0   | 8    | 0.5592          | 0.3698    | 0.6827 | 0.4797 | 0.7818   |
+| No log        | 2.0   | 16   | 0.4491          | 0.4831    | 0.8269 | 0.6099 | 0.8062   |
+| No log        | 3.0   | 24   | 0.3738          | 0.6226    | 0.9519 | 0.7529 | 0.8399   |
+| No log        | 4.0   | 32   | 0.1781          | 0.6691    | 0.8942 | 0.7654 | 0.9401   |
+| No log        | 5.0   | 40   | 0.2201          | 0.8095    | 0.9808 | 0.8870 | 0.9204   |
+| No log        | 6.0   | 48   | 0.0936          | 0.8130    | 0.9615 | 0.8811 | 0.9710   |
+| No log        | 7.0   | 56   | 0.0692          | 0.8197    | 0.9615 | 0.8850 | 0.9757   |
+| No log        | 8.0   | 64   | 0.0712          | 0.8264    | 0.9615 | 0.8889 | 0.9710   |
+| No log        | 9.0   | 72   | 0.0575          | 0.8621    | 0.9615 | 0.9091 | 0.9803   |
+| No log        | 10.0  | 80   | 0.0625          | 0.8487    | 0.9712 | 0.9058 | 0.9766   |
+| No log        | 11.0  | 88   | 0.0580          | 0.8584    | 0.9327 | 0.8940 | 0.9766   |
+| No log        | 12.0  | 96   | 0.0551          | 0.8684    | 0.9519 | 0.9083 | 0.9813   |
+| No log        | 13.0  | 104  | 0.0554          | 0.8761    | 0.9519 | 0.9124 | 0.9803   |
+| No log        | 14.0  | 112  | 0.0535          | 0.8772    | 0.9615 | 0.9174 | 0.9813   |
+| No log        | 15.0  | 120  | 0.0518          | 0.8850    | 0.9615 | 0.9217 | 0.9822   |
 
 
 ### Framework versions