Shree Ganeshay Namah, POS-MORPH Training with seqeval metrics complete

README.md

@@ -25,16 +25,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.9077441437586907
+      value: 0.9470202237521514
     - name: Recall
       type: recall
-      value: 0.9170628917224983
+      value: 0.951318348822131
     - name: F1
       type: f1
-      value: 0.9123797237004785
+      value: 0.9491644204851751
     - name: Accuracy
       type: accuracy
-      value: 0.9182290699832931
+      value: 0.9499257471691108
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -44,11 +44,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [om-ashish-soni/pos-morph-analysis-eng](https://huggingface.co/om-ashish-soni/pos-morph-analysis-eng) on the universal_dependencies dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.4982
-- Precision: 0.9077
-- Recall: 0.9171
-- F1: 0.9124
-- Accuracy: 0.9182
+- Loss: 0.2405
+- Precision: 0.9470
+- Recall: 0.9513
+- F1: 0.9492
+- Accuracy: 0.9499
 
 ## Model description
 
@@ -75,14 +75,16 @@ The following hyperparameters were used during training:
 - total_train_batch_size: 32
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 2
+- num_epochs: 4
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 99   | 0.6670          | 0.8657    | 0.8779 | 0.8718 | 0.8827   |
-| No log        | 1.99  | 198  | 0.4982          | 0.9077    | 0.9171 | 0.9124 | 0.9182   |
+| No log        | 1.0   | 99   | 0.3058          | 0.9324    | 0.9376 | 0.9350 | 0.9369   |
+| No log        | 1.99  | 198  | 0.2559          | 0.9423    | 0.9461 | 0.9442 | 0.9456   |
+| No log        | 2.99  | 297  | 0.2424          | 0.9449    | 0.9497 | 0.9473 | 0.9488   |
+| No log        | 3.99  | 396  | 0.2405          | 0.9470    | 0.9513 | 0.9492 | 0.9499   |
 
 
 ### Framework versions