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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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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: deberta-base-HSOL-WIKI-CLS |
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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-HSOL-WIKI-CLS |
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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: 1.1529 |
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- Precision: 0.7757 |
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- Recall: 0.7782 |
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- F1: 0.7769 |
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- Accuracy: 0.8075 |
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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: 3e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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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: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 0.6211 | 1.0 | 769 | 0.7439 | 0.8403 | 0.6654 | 0.6824 | 0.7854 | |
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| 0.5518 | 2.0 | 1538 | 0.4591 | 0.7945 | 0.7469 | 0.7629 | 0.8114 | |
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| 0.4051 | 3.0 | 2307 | 0.7194 | 0.7718 | 0.7674 | 0.7695 | 0.8036 | |
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| 0.2264 | 4.0 | 3076 | 0.9925 | 0.7918 | 0.7546 | 0.7682 | 0.8127 | |
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| 0.166 | 5.0 | 3845 | 1.1529 | 0.7757 | 0.7782 | 0.7769 | 0.8075 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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