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--- |
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license: mit |
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base_model: digitalepidemiologylab/covid-twitter-bert-v2 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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model-index: |
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- name: FakeNewsDetection_Cross-Sean |
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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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# FakeNewsDetection_Cross-Sean |
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This model is a fine-tuned version of [digitalepidemiologylab/covid-twitter-bert-v2](https://huggingface.co/digitalepidemiologylab/covid-twitter-bert-v2) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0824 |
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- F1: 0.9882 |
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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: 16 |
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- eval_batch_size: 16 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 0.0786 | 1.0 | 1100 | 0.0654 | 0.9845 | |
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| 0.0386 | 2.0 | 2200 | 0.0574 | 0.9852 | |
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| 0.0222 | 3.0 | 3300 | 0.0689 | 0.9864 | |
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| 0.0098 | 4.0 | 4400 | 0.0924 | 0.9848 | |
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| 0.0059 | 5.0 | 5500 | 0.0824 | 0.9882 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.2.0+cu118 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.1 |
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