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+ ---
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+ license: mit
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+ base_model: microsoft/deberta-base
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: FakeNews-deberta-base-stopwords
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # FakeNews-deberta-base-stopwords
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+
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+ This model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/microsoft/deberta-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2102
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+ - Accuracy: 0.9612
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 5
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.3343 | 1.0 | 1605 | 0.3262 | 0.9196 |
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+ | 0.3889 | 2.0 | 3210 | 0.3157 | 0.9276 |
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+ | 0.2327 | 3.0 | 4815 | 0.2983 | 0.9383 |
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+ | 0.2261 | 4.0 | 6420 | 0.2127 | 0.9528 |
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+ | 0.1629 | 5.0 | 8025 | 0.2102 | 0.9612 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.34.1
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1