End of training

README.md

@@ -1,13 +1,28 @@
 ---
 library_name: transformers
+language:
+- en
 base_model: Hartunka/bert_base_km_50_v2
 tags:
 - generated_from_trainer
+datasets:
+- glue
 metrics:
 - accuracy
 model-index:
 - name: bert_base_km_50_v2_qnli
-  results: []
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: GLUE QNLI
+      type: glue
+      args: qnli
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.6512904997254256
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -15,10 +30,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # bert_base_km_50_v2_qnli
 
-This model is a fine-tuned version of [Hartunka/bert_base_km_50_v2](https://huggingface.co/Hartunka/bert_base_km_50_v2) on an unknown dataset.
+This model is a fine-tuned version of [Hartunka/bert_base_km_50_v2](https://huggingface.co/Hartunka/bert_base_km_50_v2) on the GLUE QNLI dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.1663
-- Accuracy: 0.6451
+- Loss: 0.6248
+- Accuracy: 0.6513
 
 ## Model description
 

all_results.json

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+}

eval_results.json

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+{
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+}

logs/events.out.tfevents.1745413082.s_005_m.2876923.23

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+oid sha256:da4d0ad03a8296b34e3abf26598457cccbb1606d16efaf492f39e36b55030cc2
+size 363

train_results.json

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+}

trainer_state.json

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+  "best_model_checkpoint": "bert_base_km_50_v2_qnli/checkpoint-820",
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+}