Model save

README.md

@@ -1,7 +1,7 @@
 ---
 library_name: transformers
-license: apache-2.0
-base_model: bert-base-multilingual-cased
+license: mit
+base_model: xlm-roberta-base
 tags:
 - generated_from_trainer
 datasets:
@@ -26,16 +26,16 @@ model-index:
     metrics:
     - name: F1
       type: f1
-      value: 0.6679960119641077
+      value: 0.6381292112564407
     - name: Precision
       type: precision
-      value: 0.654296875
+      value: 0.6213817059050559
     - name: Recall
       type: recall
-      value: 0.6822810590631364
+      value: 0.6558044806517311
     - name: Accuracy
       type: accuracy
-      value: 0.9114525949550595
+      value: 0.9019425920556683
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -43,13 +43,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # turkish-ner-fold-bBERT1
 
-This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the turkish_ner dataset.
+This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the turkish_ner dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3590
-- F1: 0.6680
-- Precision: 0.6543
-- Recall: 0.6823
-- Accuracy: 0.9115
+- Loss: 0.3085
+- F1: 0.6381
+- Precision: 0.6214
+- Recall: 0.6558
+- Accuracy: 0.9019
 
 ## Model description
 
@@ -80,11 +80,11 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | F1     | Precision | Recall | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|:--------:|
-| 0.3643        | 1.0   | 500  | 0.2842          | 0.6052 | 0.6314    | 0.5811 | 0.8945   |
-| 0.2249        | 2.0   | 1000 | 0.2703          | 0.6500 | 0.6366    | 0.6640 | 0.9055   |
-| 0.1451        | 3.0   | 1500 | 0.2786          | 0.6724 | 0.6786    | 0.6664 | 0.9120   |
-| 0.0914        | 4.0   | 2000 | 0.3087          | 0.6839 | 0.6676    | 0.7011 | 0.9133   |
-| 0.0576        | 5.0   | 2500 | 0.3465          | 0.6851 | 0.6702    | 0.7007 | 0.9129   |
+| 0.4015        | 1.0   | 500  | 0.3224          | 0.5739 | 0.5628    | 0.5855 | 0.8788   |
+| 0.2729        | 2.0   | 1000 | 0.2923          | 0.6221 | 0.5852    | 0.6640 | 0.8923   |
+| 0.2098        | 3.0   | 1500 | 0.2794          | 0.6402 | 0.6451    | 0.6353 | 0.9030   |
+| 0.1613        | 4.0   | 2000 | 0.3026          | 0.6458 | 0.6236    | 0.6696 | 0.8991   |
+| 0.1269        | 5.0   | 2500 | 0.3039          | 0.6528 | 0.6420    | 0.6640 | 0.9050   |
 
 
 ### Framework versions

runs/Feb26_12-19-49_9c672336c1e1/events.out.tfevents.1740572392.9c672336c1e1.1001.0

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-size 8459
+oid sha256:4f10dd6cf50ffcb1240b5421eb387999e0d78f526aa5a879467edaf89ab4bb98
+size 9285

runs/Feb26_12-19-49_9c672336c1e1/events.out.tfevents.1740572988.9c672336c1e1.1001.1

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