Model save

README.md

@@ -1,24 +1,9 @@
 ---
 tags:
 - generated_from_trainer
-datasets:
-- akahana/GlotCC-V1-jav-Latn
-metrics:
-- accuracy
 model-index:
 - name: mini-roberta-javanese
-  results:
-  - task:
-      name: Masked Language Modeling
-      type: fill-mask
-    dataset:
-      name: akahana/GlotCC-V1-jav-Latn default
-      type: akahana/GlotCC-V1-jav-Latn
-      args: default
-    metrics:
-    - name: Accuracy
-      type: accuracy
-      value: 0.14698866640019598
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -26,10 +11,7 @@ should probably proofread and complete it, then remove this comment. -->
 
 # mini-roberta-javanese
 
-This model is a fine-tuned version of [](https://huggingface.co/) on the akahana/GlotCC-V1-jav-Latn default dataset.
-It achieves the following results on the evaluation set:
-- Loss: 6.3746
-- Accuracy: 0.1470
+This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
 
 ## Model description
 
@@ -54,7 +36,7 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 15.0
+- num_epochs: 30.0
 - mixed_precision_training: Native AMP
 
 ### Training results