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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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