update model card README.md

README.md

@@ -4,9 +4,22 @@ tags:
 - generated_from_trainer
 datasets:
 - clinc_oos
+metrics:
+- accuracy
 model-index:
 - name: distilbert-base-uncased-finetuned-clinc
-  results: []
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: clinc_oos
+      type: clinc_oos
+      args: plus
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9474193548387096
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -15,6 +28,9 @@ should probably proofread and complete it, then remove this comment. -->
 # distilbert-base-uncased-finetuned-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: 0.2454
+- Accuracy: 0.9474
 
 ## Model description
 
@@ -34,16 +50,27 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
-- train_batch_size: 48
-- eval_batch_size: 48
+- train_batch_size: 16
+- eval_batch_size: 16
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - num_epochs: 5
 
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 3.496         | 1.0   | 954  | 1.8019          | 0.8306   |
+| 1.0663        | 2.0   | 1908 | 0.5690          | 0.9174   |
+| 0.3267        | 3.0   | 2862 | 0.3128          | 0.9406   |
+| 0.1397        | 4.0   | 3816 | 0.2567          | 0.9445   |
+| 0.0846        | 5.0   | 4770 | 0.2454          | 0.9474   |
+
+
 ### Framework versions
 
-- Transformers 4.11.3
-- Pytorch 1.11.0+cu113
+- Transformers 4.19.2
+- Pytorch 1.11.0
 - Datasets 1.16.1
-- Tokenizers 0.10.3
+- Tokenizers 0.12.1