End of training

README.md

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+---
+license: mit
+base_model: microsoft/deberta-large
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: FakeNews-deberta-large-stable
+  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-large-stable
+
+This model is a fine-tuned version of [microsoft/deberta-large](https://huggingface.co/microsoft/deberta-large) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1048
+- Accuracy: 0.9771
+
+## 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-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-06
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.3373        | 1.0   | 802  | 0.1635          | 0.9682   |
+| 0.0951        | 2.0   | 1605 | 0.1048          | 0.9771   |
+| 0.0419        | 3.0   | 2407 | 0.1141          | 0.9785   |
+| 0.0114        | 4.0   | 3210 | 0.1555          | 0.9818   |
+| 0.0026        | 5.0   | 4010 | 0.1680          | 0.9808   |
+
+
+### Framework versions
+
+- Transformers 4.35.0
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1

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