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End of training
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README.md
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---
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license: mit
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base_model: microsoft/deberta-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: deberta-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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# deberta-base-clickbait-task1-20-epoch-post_title
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This model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/microsoft/deberta-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.5412
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- Accuracy: 0.7025
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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 | 0.7414 | 0.7075 |
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| No log | 2.0 | 400 | 0.6972 | 0.73 |
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| 0.7437 | 3.0 | 600 | 0.7188 | 0.73 |
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| 0.7437 | 4.0 | 800 | 0.9260 | 0.7225 |
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| 0.3148 | 5.0 | 1000 | 1.0694 | 0.715 |
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| 0.3148 | 6.0 | 1200 | 1.3980 | 0.735 |
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| 0.3148 | 7.0 | 1400 | 1.6897 | 0.7125 |
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| 0.103 | 8.0 | 1600 | 1.8628 | 0.7275 |
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| 0.103 | 9.0 | 1800 | 2.0991 | 0.7125 |
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| 0.0456 | 10.0 | 2000 | 2.0466 | 0.7225 |
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| 0.0456 | 11.0 | 2200 | 2.2220 | 0.7225 |
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| 0.0456 | 12.0 | 2400 | 2.3278 | 0.6975 |
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| 0.0222 | 13.0 | 2600 | 2.4275 | 0.7025 |
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| 0.0222 | 14.0 | 2800 | 2.4249 | 0.695 |
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| 0.0092 | 15.0 | 3000 | 2.4740 | 0.7275 |
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| 0.0092 | 16.0 | 3200 | 2.4897 | 0.7125 |
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| 0.0092 | 17.0 | 3400 | 2.5280 | 0.705 |
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| 0.0058 | 18.0 | 3600 | 2.5360 | 0.705 |
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| 0.0058 | 19.0 | 3800 | 2.5075 | 0.715 |
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| 0.0039 | 20.0 | 4000 | 2.5412 | 0.7025 |
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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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model.safetensors
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