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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-v3-base-orgs-v1 |
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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-orgs-v1 |
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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: 0.1186 |
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- Precision: 0.8127 |
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- Recall: 0.7735 |
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- F1: 0.7927 |
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- Accuracy: 0.9632 |
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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: 128 |
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- eval_batch_size: 256 |
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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: 3.0 |
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- mixed_precision_training: Native AMP |
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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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| 0.0706 | 0.7 | 600 | 0.1138 | 0.7590 | 0.7793 | 0.7690 | 0.9602 | |
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| 0.0526 | 1.4 | 1200 | 0.1113 | 0.7942 | 0.7799 | 0.7870 | 0.9617 | |
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| 0.0409 | 2.11 | 1800 | 0.1125 | 0.7911 | 0.7839 | 0.7875 | 0.9627 | |
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| 0.0376 | 2.81 | 2400 | 0.1186 | 0.8127 | 0.7735 | 0.7927 | 0.9632 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0a0+32f93b1 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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