update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- clinc_oos
+metrics:
+- accuracy
+model-index:
+- name: distilbert-base-uncased-distilled-clinc
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: clinc_oos
+      type: clinc_oos
+      args: plus
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9438709677419355
+---
+
+<!-- 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. -->
+
+# distilbert-base-uncased-distilled-clinc
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the clinc_oos dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2108
+- Accuracy: 0.9439
+
+## 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: 2e-05
+- train_batch_size: 48
+- eval_batch_size: 48
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 9
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.0011        | 1.0   | 318  | 1.4515          | 0.7655   |
+| 1.142         | 2.0   | 636  | 0.7762          | 0.87     |
+| 0.6315        | 3.0   | 954  | 0.4564          | 0.9171   |
+| 0.3865        | 4.0   | 1272 | 0.3170          | 0.9329   |
+| 0.2678        | 5.0   | 1590 | 0.2573          | 0.9426   |
+| 0.2125        | 6.0   | 1908 | 0.2316          | 0.9432   |
+| 0.184         | 7.0   | 2226 | 0.2185          | 0.9432   |
+| 0.1699        | 8.0   | 2544 | 0.2124          | 0.9445   |
+| 0.1638        | 9.0   | 2862 | 0.2108          | 0.9439   |
+
+
+### Framework versions
+
+- Transformers 4.11.3
+- Pytorch 1.12.1+cu113
+- Datasets 1.16.1
+- Tokenizers 0.10.3