Training complete
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README.md
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---
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base_model: mor40/BulBERT-chitanka-model
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tags:
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- generated_from_trainer
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datasets:
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- bgglue
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metrics:
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- accuracy
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model-index:
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- name: BulBERT-fakenews-5epochs
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results:
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- task:
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name: Text Classification
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type: text-classification
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dataset:
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name: bgglue
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type: bgglue
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config: fakenews
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split: validation
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args: fakenews
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9049773755656109
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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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# BulBERT-fakenews-5epochs
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This model is a fine-tuned version of [mor40/BulBERT-chitanka-model](https://huggingface.co/mor40/BulBERT-chitanka-model) on the bgglue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3487
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- Accuracy: 0.9050
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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: 2e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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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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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| No log | 1.0 | 84 | 0.4732 | 0.7511 |
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| No log | 2.0 | 168 | 0.3922 | 0.8552 |
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| No log | 3.0 | 252 | 0.3230 | 0.8778 |
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| No log | 4.0 | 336 | 0.3518 | 0.8959 |
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| No log | 5.0 | 420 | 0.3487 | 0.9050 |
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### Framework versions
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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
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