End of training

README.md

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+---
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+datasets:
+- clinc_oos
+metrics:
+- accuracy
+model-index:
+- name: bert-base-uncased-finetuned-clinc_oos-distilled-clinc_oos
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: clinc_oos
+      type: clinc_oos
+      config: plus
+      split: validation
+      args: plus
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9158064516129032
+---
+
+<!-- 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-distilled-clinc_oos
+
+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: 0.7724
+- Accuracy: 0.9158
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 318  | 3.2762          | 0.7284   |
+| 3.7824        | 2.0   | 636  | 1.8624          | 0.8358   |
+| 3.7824        | 3.0   | 954  | 1.1512          | 0.8984   |
+| 1.6858        | 4.0   | 1272 | 0.8540          | 0.9132   |
+| 0.8983        | 5.0   | 1590 | 0.7724          | 0.9158   |
+
+
+### Framework versions
+
+- Transformers 4.33.3
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.13.3

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