| --- |
| 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 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.35.0 |
| - Pytorch 2.1.0+cu118 |
| - Datasets 2.14.6 |
| - Tokenizers 0.14.1 |
|
|
