update model card README.md

README.md

@@ -1,76 +1,76 @@
----
-license: apache-2.0
-tags:
-- generated_from_trainer
-datasets:
-- clinc_oos
-metrics:
-- accuracy
-model-index:
-- name: distilbert-base-uncased-finetuned-clinc
-  results:
-  - task:
-      name: Text Classification
-      type: text-classification
-    dataset:
-      name: clinc_oos
-      type: clinc_oos
-      args: plus
-    metrics:
-    - name: Accuracy
-      type: accuracy
-      value: 0.9167741935483871
----
-
-<!-- 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-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: 0.7778
-- Accuracy: 0.9168
-
-## 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: 5
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 4.2883        | 1.0   | 318  | 3.2779          | 0.7394   |
-| 2.623         | 2.0   | 636  | 1.8741          | 0.8287   |
-| 1.544         | 3.0   | 954  | 1.1618          | 0.89     |
-| 1.0111        | 4.0   | 1272 | 0.8601          | 0.9090   |
-| 0.7998        | 5.0   | 1590 | 0.7778          | 0.9168   |
-
-
-### Framework versions
-
-- Transformers 4.11.3
-- Pytorch 1.12.1+cu113
-- Datasets 1.16.1
-- Tokenizers 0.10.3
+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- clinc_oos
+metrics:
+- accuracy
+model-index:
+- name: distilbert-base-uncased-finetuned-clinc
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: clinc_oos
+      type: clinc_oos
+      args: plus
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9170967741935484
+---
+
+<!-- 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-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: 0.7778
+- Accuracy: 0.9171
+
+## 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: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 4.2882        | 1.0   | 318  | 3.2777          | 0.7390   |
+| 2.6228        | 2.0   | 636  | 1.8739          | 0.8287   |
+| 1.5439        | 3.0   | 954  | 1.1619          | 0.8894   |
+| 1.0111        | 4.0   | 1272 | 0.8601          | 0.9094   |
+| 0.7999        | 5.0   | 1590 | 0.7778          | 0.9171   |
+
+
+### Framework versions
+
+- Transformers 4.11.3
+- Pytorch 1.12.1+cpu
+- Datasets 2.4.0
+- Tokenizers 0.10.3