End of training
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README.md
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---
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license: mit
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base_model: microsoft/deberta-large
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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-large-grad
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results: []
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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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# FakeNews-deberta-large-grad
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This model is a fine-tuned version of [microsoft/deberta-large](https://huggingface.co/microsoft/deberta-large) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4159
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- Accuracy: 0.8547
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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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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- gradient_accumulation_steps: 2
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- total_train_batch_size: 8
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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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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.5255 | 1.0 | 802 | 0.4159 | 0.8547 |
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| 0.4852 | 2.0 | 1605 | 0.4894 | 0.7631 |
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| 0.4849 | 3.0 | 2407 | 0.4670 | 0.7710 |
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| 0.4839 | 4.0 | 3210 | 0.4664 | 0.7729 |
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| 0.5581 | 5.0 | 4010 | 0.7548 | 0.4766 |
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### Framework versions
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- Transformers 4.35.0
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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
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