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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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- 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-v3-large-finetuned-ner |
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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-v3-large-finetuned-ner |
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This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co./microsoft/deberta-v3-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0364 |
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- Precision: 0.9641 |
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- Recall: 0.9716 |
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- F1: 0.9678 |
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- Accuracy: 0.9931 |
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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: 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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| 0.1237 | 1.0 | 878 | 0.0406 | 0.9492 | 0.9589 | 0.9540 | 0.9906 | |
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| 0.0242 | 2.0 | 1756 | 0.0340 | 0.9550 | 0.9634 | 0.9592 | 0.9917 | |
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| 0.0123 | 3.0 | 2634 | 0.0383 | 0.9630 | 0.9679 | 0.9654 | 0.9923 | |
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| 0.0055 | 4.0 | 3512 | 0.0345 | 0.9633 | 0.9716 | 0.9674 | 0.9929 | |
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| 0.0034 | 5.0 | 4390 | 0.0364 | 0.9641 | 0.9716 | 0.9678 | 0.9931 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.2.0 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
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