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--- |
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license: mit |
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base_model: microsoft/deberta-v3-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-finetuned-ner-copious |
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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-finetuned-ner-copious |
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This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0499 |
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- Precision: 0.7867 |
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- Recall: 0.8333 |
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- F1: 0.8094 |
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- Accuracy: 0.9842 |
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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: 8 |
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- eval_batch_size: 8 |
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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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| No log | 1.0 | 63 | 0.0632 | 0.6793 | 0.7383 | 0.7076 | 0.9789 | |
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| No log | 2.0 | 126 | 0.0507 | 0.7559 | 0.8320 | 0.7921 | 0.9837 | |
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| No log | 3.0 | 189 | 0.0517 | 0.7771 | 0.8306 | 0.8029 | 0.9840 | |
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| No log | 4.0 | 252 | 0.0517 | 0.7822 | 0.8457 | 0.8127 | 0.9839 | |
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| No log | 5.0 | 315 | 0.0499 | 0.7867 | 0.8333 | 0.8094 | 0.9842 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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