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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-gpu
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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-gpu
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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: 0.0130
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- Accuracy: 0.9976
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- F1: 0.9976
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- Precision: 0.9976
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- Recall: 0.9976
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- Accuracy Label Clickbait: 0.9933
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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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| 0.0546 | 0.4831 | 100 | 0.0504 | 0.9902 | 0.9902 | 0.9902 | 0.9902 | 0.9866 | 0.9923 |
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| 0.0071 | 0.9662 | 200 | 0.0060 | 0.9988 | 0.9988 | 0.9988 | 0.9988 | 0.9967 | 1.0 |
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| 0.0008 | 1.4493 | 300 | 0.0088 | 0.9976 | 0.9976 | 0.9976 | 0.9976 | 0.9933 | 1.0 |
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| 0.0006 | 1.9324 | 400 | 0.0310 | 0.9939 | 0.9939 | 0.9939 | 0.9939 | 0.9833 | 1.0 |
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| 0.0007 | 2.4155 | 500 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
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| 0.0009 | 2.8986 | 600 | 0.0079 | 0.9988 | 0.9988 | 0.9988 | 0.9988 | 0.9967 | 1.0 |
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 2.3.0+cu118
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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