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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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model-index: |
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- name: fatimah_fake_news_bert |
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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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# fatimah_fake_news_bert |
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This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on [Fake and real dataset on kaggle ]([distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english)) |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0010 |
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- Accuracy: 0.9998 |
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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: 10 |
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- eval_batch_size: 20 |
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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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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 1 |
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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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| 0.3298 | 0.06 | 200 | 0.0094 | 0.9987 | |
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| 0.0087 | 0.11 | 400 | 0.0091 | 0.9988 | |
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| 0.0126 | 0.17 | 600 | 0.0132 | 0.9965 | |
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| 0.0081 | 0.22 | 800 | 0.0100 | 0.9987 | |
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| 0.0132 | 0.28 | 1000 | 0.0086 | 0.9990 | |
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| 0.0131 | 0.33 | 1200 | 0.0070 | 0.9986 | |
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| 0.0086 | 0.39 | 1400 | 0.0079 | 0.9990 | |
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| 0.0041 | 0.45 | 1600 | 0.0057 | 0.9991 | |
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| 0.0069 | 0.5 | 1800 | 0.0083 | 0.9989 | |
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| 0.0052 | 0.56 | 2000 | 0.0043 | 0.9993 | |
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| 0.0 | 0.61 | 2200 | 0.0047 | 0.9993 | |
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| 0.003 | 0.67 | 2400 | 0.0052 | 0.9994 | |
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| 0.0126 | 0.72 | 2600 | 0.0028 | 0.9997 | |
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| 0.0047 | 0.78 | 2800 | 0.0018 | 0.9996 | |
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| 0.0 | 0.84 | 3000 | 0.0027 | 0.9996 | |
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| 0.0001 | 0.89 | 3200 | 0.0029 | 0.9996 | |
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| 0.0079 | 0.95 | 3400 | 0.0010 | 0.9998 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 2.0.0 |
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- Tokenizers 0.11.6 |
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