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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-stable |
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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-stable |
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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: 0.1048 |
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- Accuracy: 0.9771 |
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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: 3e-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-06 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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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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| 0.3373 | 1.0 | 802 | 0.1635 | 0.9682 | |
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| 0.0951 | 2.0 | 1605 | 0.1048 | 0.9771 | |
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| 0.0419 | 3.0 | 2407 | 0.1141 | 0.9785 | |
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| 0.0114 | 4.0 | 3210 | 0.1555 | 0.9818 | |
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| 0.0026 | 5.0 | 4010 | 0.1680 | 0.9808 | |
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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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