Model save

README.md

@@ -3,26 +3,9 @@ license: mit
 base_model: w11wo/indo-roberta-small
 tags:
 - generated_from_trainer
-datasets:
-- indonlu
-metrics:
-- accuracy
 model-index:
 - name: indo-roberta-small-finetuned-indonlu-smsa
-  results:
-  - task:
-      name: Text Classification
-      type: text-classification
-    dataset:
-      name: indonlu
-      type: indonlu
-      config: smsa
-      split: validation
-      args: smsa
-    metrics:
-    - name: Accuracy
-      type: accuracy
-      value: 0.888095238095238
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -30,10 +13,7 @@ should probably proofread and complete it, then remove this comment. -->
 
 # indo-roberta-small-finetuned-indonlu-smsa
 
-This model is a fine-tuned version of [w11wo/indo-roberta-small](https://huggingface.co/w11wo/indo-roberta-small) on the indonlu dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.4497
-- Accuracy: 0.8881
+This model is a fine-tuned version of [w11wo/indo-roberta-small](https://huggingface.co/w11wo/indo-roberta-small) on an unknown dataset.
 
 ## Model description
 
@@ -61,25 +41,9 @@ The following hyperparameters were used during training:
 - lr_scheduler_warmup_steps: 1000
 - num_epochs: 10
 
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 1.0   | 172  | 0.6502          | 0.7143   |
-| No log        | 2.0   | 344  | 0.4720          | 0.8127   |
-| 0.6168        | 3.0   | 516  | 0.4511          | 0.8357   |
-| 0.6168        | 4.0   | 688  | 0.3825          | 0.8540   |
-| 0.6168        | 5.0   | 860  | 0.3655          | 0.8595   |
-| 0.2954        | 6.0   | 1032 | 0.3672          | 0.8683   |
-| 0.2954        | 7.0   | 1204 | 0.3839          | 0.8746   |
-| 0.2954        | 8.0   | 1376 | 0.4220          | 0.8706   |
-| 0.1328        | 9.0   | 1548 | 0.4497          | 0.8881   |
-| 0.1328        | 10.0  | 1720 | 0.4455          | 0.8865   |
-
-
 ### Framework versions
 
-- Transformers 4.38.2
-- Pytorch 2.1.0+cu121
-- Datasets 2.18.0
-- Tokenizers 0.15.2
+- Transformers 4.41.1
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1