End of training

README.md

@@ -26,16 +26,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.9567795201418519
+      value: 0.9574114124105806
     - name: Recall
       type: recall
-      value: 0.965986013986014
+      value: 0.9658741258741259
     - name: F1
       type: f1
-      value: 0.9613607260174823
+      value: 0.961624150607107
     - name: Accuracy
       type: accuracy
-      value: 0.9808251841548746
+      value: 0.9810238869097464
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -45,11 +45,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [PlanTL-GOB-ES/roberta-large-bne-capitel-ner](https://huggingface.co/PlanTL-GOB-ES/roberta-large-bne-capitel-ner) on the biobert_json dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0920
-- Precision: 0.9568
-- Recall: 0.9660
-- F1: 0.9614
-- Accuracy: 0.9808
+- Loss: 0.0918
+- Precision: 0.9574
+- Recall: 0.9659
+- F1: 0.9616
+- Accuracy: 0.9810
 
 ## Model description
 
@@ -80,11 +80,11 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.1281        | 1.0   | 1224 | 0.0950          | 0.9426    | 0.9555 | 0.9490 | 0.9746   |
-| 0.0866        | 2.0   | 2448 | 0.0912          | 0.9470    | 0.9679 | 0.9573 | 0.9786   |
-| 0.0503        | 3.0   | 3672 | 0.0838          | 0.9545    | 0.9698 | 0.9621 | 0.9811   |
-| 0.0319        | 4.0   | 4896 | 0.0892          | 0.9596    | 0.9673 | 0.9634 | 0.9812   |
-| 0.0187        | 5.0   | 6120 | 0.0920          | 0.9568    | 0.9660 | 0.9614 | 0.9808   |
+| 0.1292        | 1.0   | 1224 | 0.0942          | 0.9455    | 0.9528 | 0.9491 | 0.9737   |
+| 0.0813        | 2.0   | 2448 | 0.0960          | 0.9443    | 0.9696 | 0.9568 | 0.9780   |
+| 0.0509        | 3.0   | 3672 | 0.0819          | 0.9559    | 0.9686 | 0.9622 | 0.9814   |
+| 0.0314        | 4.0   | 4896 | 0.0853          | 0.9557    | 0.9694 | 0.9625 | 0.9811   |
+| 0.0196        | 5.0   | 6120 | 0.0918          | 0.9574    | 0.9659 | 0.9616 | 0.9810   |
 
 
 ### Framework versions

runs/Dec13_00-26-54_ec9b8fdfa8a5/events.out.tfevents.1734049618.ec9b8fdfa8a5.1390.0

@@ -1,3 +1,3 @@
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-size 11053
+oid sha256:47cbb80ab221940e826666fbbd246f1d74cbe0ab4e4d00157df1062f96b37b85
+size 11879