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--- |
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license: mit |
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base_model: microsoft/deberta-v3-large |
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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-large-ReqORNot |
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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-large-ReqORNot |
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This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co./microsoft/deberta-v3-large) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5297 |
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- Accuracy: 0.9135 |
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- Weighted precision: 0.9135 |
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- Weighted recall: 0.9135 |
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- Weighted f1: 0.9134 |
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- Macro precision: 0.9135 |
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- Macro recall: 0.9128 |
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- Macro f1: 0.9131 |
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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: 3 |
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- eval_batch_size: 3 |
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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: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted precision | Weighted recall | Weighted f1 | Macro precision | Macro recall | Macro f1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------------------:|:---------------:|:-----------:|:---------------:|:------------:|:--------:| |
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| 0.4826 | 1.0 | 1896 | 0.4286 | 0.9020 | 0.9020 | 0.9020 | 0.9019 | 0.9018 | 0.9014 | 0.9016 | |
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| 0.3429 | 2.0 | 3792 | 0.4274 | 0.9077 | 0.9091 | 0.9077 | 0.9078 | 0.9076 | 0.9089 | 0.9076 | |
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| 0.1299 | 3.0 | 5688 | 0.5297 | 0.9135 | 0.9135 | 0.9135 | 0.9134 | 0.9135 | 0.9128 | 0.9131 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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