End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: bert-base-cased
+tags:
+- generated_from_trainer
+datasets:
+- liar
+metrics:
+- accuracy
+model-index:
+- name: liar_binaryclassifier_distilbert_cased
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: liar
+      type: liar
+      config: default
+      split: test
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.6464208242950108
+---
+
+<!-- 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. -->
+
+# liar_binaryclassifier_distilbert_cased
+
+This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the liar dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6488
+- Model Preparation Time: 0.0055
+- Accuracy: 0.6464
+
+## 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: 3e-06
+- train_batch_size: 8
+- eval_batch_size: 8
+- 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 | Model Preparation Time | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:----------------------:|:--------:|
+| 0.6836        | 1.0   | 461  | 0.6520          | 0.0055                 | 0.6226   |
+| 0.6423        | 2.0   | 922  | 0.6326          | 0.0055                 | 0.6399   |
+| 0.6091        | 3.0   | 1383 | 0.6362          | 0.0055                 | 0.6443   |
+| 0.5843        | 4.0   | 1844 | 0.6422          | 0.0055                 | 0.6551   |
+| 0.5624        | 5.0   | 2305 | 0.6488          | 0.0055                 | 0.6464   |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.0
+- Tokenizers 0.19.1

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