End of training

README.md

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+---
+license: apache-2.0
+base_model: bert-base-uncased
+tags:
+- generated_from_trainer
+datasets:
+- clinc_oos
+metrics:
+- accuracy
+- f1
+model-index:
+- name: bert-base-uncased-finetuned-clinc_oos
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: clinc_oos
+      type: clinc_oos
+      config: plus
+      split: test
+      args: plus
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value:
+        accuracy: 0.8672727272727273
+    - name: F1
+      type: f1
+      value:
+        f1: 0.8593551627139002
+---
+
+<!-- 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. -->
+
+# bert-base-uncased-finetuned-clinc_oos
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the clinc_oos dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0863
+- Accuracy: {'accuracy': 0.8672727272727273}
+- F1: {'f1': 0.8593551627139002}
+
+## 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: 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: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy                         | F1                         |
+|:-------------:|:-----:|:----:|:---------------:|:--------------------------------:|:--------------------------:|
+| 4.3415        | 1.0   | 954  | 2.4724          | {'accuracy': 0.7769090909090909} | {'f1': 0.7596942777117995} |
+| 1.7949        | 2.0   | 1908 | 1.3415          | {'accuracy': 0.8538181818181818} | {'f1': 0.8441232118060242} |
+| 0.8898        | 3.0   | 2862 | 1.0863          | {'accuracy': 0.8672727272727273} | {'f1': 0.8593551627139002} |
+
+
+### Framework versions
+
+- Transformers 4.33.3
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.13.3

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