End of training

README.md

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+---
+license: mit
+base_model: microsoft/deberta-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: FakeNews-deberta-base-grad
+  results: []
+---
+
+<!-- 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. -->
+
+# FakeNews-deberta-base-grad
+
+This model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/microsoft/deberta-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1432
+- Accuracy: 0.9752
+
+## 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: 5e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 8
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.2381        | 1.0   | 802  | 0.1649          | 0.9650   |
+| 0.1036        | 2.0   | 1605 | 0.2492          | 0.9570   |
+| 0.0441        | 3.0   | 2407 | 0.1432          | 0.9752   |
+| 0.0183        | 4.0   | 3210 | 0.1545          | 0.9757   |
+| 0.0055        | 5.0   | 4010 | 0.1595          | 0.9790   |
+
+
+### Framework versions
+
+- Transformers 4.35.0
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1

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