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--- |
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license: apache-2.0 |
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base_model: albert/albert-base-v2 |
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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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- precision |
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- recall |
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model-index: |
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- name: classify-clickbait |
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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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# classify-clickbait |
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This model is a fine-tuned version of [albert/albert-base-v2](https://huggingface.co./albert/albert-base-v2) on an unknown dataset. |
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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: 1.0 |
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- F1: 1.0 |
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- Precision: 1.0 |
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- Recall: 1.0 |
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- Accuracy Label Clickbait: 1.0 |
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- Accuracy Label Factual: 1.0 |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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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: 500 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Accuracy Label Clickbait | Accuracy Label Factual | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:------------------------:|:----------------------:| |
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| 0.1089 | 1.1628 | 100 | 0.0617 | 0.9884 | 0.9884 | 0.9884 | 0.9884 | 0.9828 | 0.9941 | |
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| 0.0118 | 2.3256 | 200 | 0.0093 | 0.9971 | 0.9971 | 0.9971 | 0.9971 | 0.9943 | 1.0 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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