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README.md
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---
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base_model: eclec/patentClassificationLongFormer2
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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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model-index:
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- name: patentClassificationLongFormer3
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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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# patentClassificationLongFormer3
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This model is a fine-tuned version of [eclec/patentClassificationLongFormer2](https://huggingface.co/eclec/patentClassificationLongFormer2) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4177
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- Accuracy: 0.8029
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- F1: 0.5802
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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: 1.3494108617032343e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 11
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 64
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.17770742346220472
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- lr_scheduler_warmup_steps: 59
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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 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| No log | 1.0 | 212 | 0.4189 | 0.8032 | 0.5967 |
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| No log | 2.0 | 425 | 0.4177 | 0.8029 | 0.5802 |
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| 0.4021 | 2.99 | 636 | 0.4360 | 0.8041 | 0.5978 |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.0
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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