update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- indonlu
+metrics:
+- accuracy
+- f1
+model-index:
+- name: indobert-distilled-optimized-for-classification
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: indonlu
+      type: indonlu
+      args: smsa
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9023809523809524
+    - name: F1
+      type: f1
+      value: 0.9020516403647337
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# indobert-distilled-optimized-for-classification
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the indonlu dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5991
+- Accuracy: 0.9024
+- F1: 0.9021
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5.262995179171344e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 33
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| 1.2938        | 1.0   | 688  | 0.8433          | 0.8484   | 0.8513 |
+| 0.711         | 2.0   | 1376 | 0.6408          | 0.8881   | 0.8878 |
+| 0.4416        | 3.0   | 2064 | 0.7964          | 0.8794   | 0.8793 |
+| 0.2907        | 4.0   | 2752 | 0.7559          | 0.8897   | 0.8900 |
+| 0.2065        | 5.0   | 3440 | 0.6892          | 0.8968   | 0.8974 |
+| 0.1574        | 6.0   | 4128 | 0.6881          | 0.8913   | 0.8906 |
+| 0.1131        | 7.0   | 4816 | 0.6224          | 0.8984   | 0.8982 |
+| 0.0865        | 8.0   | 5504 | 0.6312          | 0.8976   | 0.8970 |
+| 0.0678        | 9.0   | 6192 | 0.6187          | 0.8992   | 0.8989 |
+| 0.0526        | 10.0  | 6880 | 0.5991          | 0.9024   | 0.9021 |
+
+
+### Framework versions
+
+- Transformers 4.18.0
+- Pytorch 1.10.0+cu111
+- Datasets 2.1.0
+- Tokenizers 0.12.1