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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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datasets: |
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- ontonotes5 |
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model-index: |
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- name: deberta-v3-base_on5 |
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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-base_on5 |
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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 ontonotes5 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0598 |
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- F1-type-match: 0.6780 |
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- F1-partial: 0.6872 |
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- F1-strict: 0.6565 |
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- F1-exact: 0.6729 |
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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: 0.0001 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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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: linear |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1-type-match | F1-partial | F1-strict | F1-exact | |
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|:-------------:|:-----:|:----:|:---------------:|:-------------:|:----------:|:---------:|:--------:| |
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| 0.0738 | 1.0 | 936 | 0.0624 | 0.5568 | 0.5632 | 0.5322 | 0.5479 | |
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| 0.0432 | 2.0 | 1873 | 0.0591 | 0.5773 | 0.5848 | 0.5559 | 0.5709 | |
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| 0.0289 | 3.0 | 2808 | 0.0598 | 0.6780 | 0.6872 | 0.6565 | 0.6729 | |
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### Framework versions |
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- Transformers 4.36.0 |
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- Pytorch 2.0.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.15.0 |
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