Model save

README.md

@@ -25,16 +25,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.8556554661618552
+      value: 0.8566729323308271
     - name: Recall
       type: recall
-      value: 0.8972704714640198
+      value: 0.9047146401985111
     - name: F1
       type: f1
-      value: 0.8759689922480619
+      value: 0.8800386193579531
     - name: Accuracy
       type: accuracy
-      value: 0.9759953161592506
+      value: 0.9771662763466042
 ---
 
 <!-- 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 [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the cnec dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1541
-- Precision: 0.8557
-- Recall: 0.8973
-- F1: 0.8760
-- Accuracy: 0.9760
+- Loss: 0.1471
+- Precision: 0.8567
+- Recall: 0.9047
+- F1: 0.8800
+- Accuracy: 0.9772
 
 ## Model description
 
@@ -79,14 +79,14 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.2518        | 1.12  | 500  | 0.1312          | 0.7219    | 0.8427 | 0.7777 | 0.9649   |
-| 0.0996        | 2.24  | 1000 | 0.1222          | 0.8003    | 0.8511 | 0.8249 | 0.9677   |
-| 0.0652        | 3.36  | 1500 | 0.1259          | 0.8137    | 0.8734 | 0.8425 | 0.9730   |
-| 0.0421        | 4.47  | 2000 | 0.1293          | 0.8306    | 0.8859 | 0.8573 | 0.9739   |
-| 0.0277        | 5.59  | 2500 | 0.1519          | 0.8320    | 0.8799 | 0.8553 | 0.9742   |
-| 0.0169        | 6.71  | 3000 | 0.1342          | 0.8516    | 0.8968 | 0.8736 | 0.9756   |
-| 0.0116        | 7.83  | 3500 | 0.1496          | 0.8540    | 0.8973 | 0.8751 | 0.9760   |
-| 0.0065        | 8.95  | 4000 | 0.1541          | 0.8557    | 0.8973 | 0.8760 | 0.9760   |
+| 0.2836        | 1.12  | 500  | 0.1341          | 0.7486    | 0.8467 | 0.7946 | 0.9649   |
+| 0.116         | 2.24  | 1000 | 0.1048          | 0.7866    | 0.8655 | 0.8242 | 0.9734   |
+| 0.0832        | 3.36  | 1500 | 0.1066          | 0.7967    | 0.8734 | 0.8333 | 0.9746   |
+| 0.0577        | 4.47  | 2000 | 0.1112          | 0.8408    | 0.8834 | 0.8616 | 0.9753   |
+| 0.0445        | 5.59  | 2500 | 0.1378          | 0.8384    | 0.8883 | 0.8627 | 0.9751   |
+| 0.0337        | 6.71  | 3000 | 0.1272          | 0.8505    | 0.8978 | 0.8735 | 0.9770   |
+| 0.025         | 7.83  | 3500 | 0.1447          | 0.8462    | 0.9007 | 0.8726 | 0.9760   |
+| 0.0191        | 8.95  | 4000 | 0.1471          | 0.8567    | 0.9047 | 0.8800 | 0.9772   |
 
 
 ### Framework versions

runs/Feb26_21-46-14_n29/events.out.tfevents.1708980375.n29.40136.0

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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-size 9906
+oid sha256:43e66b1e6184ed86aadd0c3aab401d681278b0d836dd22afc4c53c690064810b
+size 10260