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--- |
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license: mit |
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base_model: thenlper/gte-base |
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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: gte-base-clickbait-task1-20-epoch-post_title |
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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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# gte-base-clickbait-task1-20-epoch-post_title |
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This model is a fine-tuned version of [thenlper/gte-base](https://huggingface.co/thenlper/gte-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.1698 |
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- Accuracy: 0.7125 |
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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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- 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: 20 |
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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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| No log | 1.0 | 200 | 0.8221 | 0.67 | |
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| No log | 2.0 | 400 | 0.7310 | 0.7075 | |
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| 0.8027 | 3.0 | 600 | 0.7771 | 0.6975 | |
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| 0.8027 | 4.0 | 800 | 0.9364 | 0.6925 | |
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| 0.3367 | 5.0 | 1000 | 1.0995 | 0.685 | |
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| 0.3367 | 6.0 | 1200 | 1.3589 | 0.695 | |
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| 0.3367 | 7.0 | 1400 | 1.5960 | 0.69 | |
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| 0.0659 | 8.0 | 1600 | 1.7658 | 0.6925 | |
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| 0.0659 | 9.0 | 1800 | 1.8539 | 0.7075 | |
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| 0.0186 | 10.0 | 2000 | 1.9483 | 0.705 | |
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| 0.0186 | 11.0 | 2200 | 2.0515 | 0.69 | |
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| 0.0186 | 12.0 | 2400 | 2.0866 | 0.6775 | |
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| 0.0073 | 13.0 | 2600 | 2.1074 | 0.6925 | |
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| 0.0073 | 14.0 | 2800 | 2.1309 | 0.7075 | |
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| 0.0068 | 15.0 | 3000 | 2.1519 | 0.72 | |
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| 0.0068 | 16.0 | 3200 | 2.1612 | 0.7175 | |
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| 0.0068 | 17.0 | 3400 | 2.1304 | 0.715 | |
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| 0.003 | 18.0 | 3600 | 2.1813 | 0.71 | |
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| 0.003 | 19.0 | 3800 | 2.1652 | 0.7125 | |
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| 0.0029 | 20.0 | 4000 | 2.1698 | 0.7125 | |
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### Framework versions |
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- Transformers 4.44.0.dev0 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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