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--- |
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license: apache-2.0 |
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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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- f1 |
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model-index: |
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- name: bert-base-uncased-finetuned-fakenews |
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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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# bert-base-uncased-finetuned-fakenews |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0656 |
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- Accuracy: 0.9901 |
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- F1: 0.9909 |
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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: 8 |
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- eval_batch_size: 8 |
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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: 6 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:| |
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| 0.0505 | 1.0 | 3045 | 0.2405 | 0.9651 | 0.9685 | |
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| 0.0463 | 2.0 | 6090 | 0.0473 | 0.9872 | 0.9881 | |
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| 0.0272 | 3.0 | 9135 | 0.0607 | 0.9892 | 0.9900 | |
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| 0.0154 | 4.0 | 12180 | 0.0522 | 0.9892 | 0.9900 | |
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| 0.0047 | 5.0 | 15225 | 0.0717 | 0.9895 | 0.9903 | |
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| 0.0024 | 6.0 | 18270 | 0.0656 | 0.9901 | 0.9909 | |
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### Framework versions |
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- Transformers 4.22.0 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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