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license: mit |
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tags: |
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- text-classification |
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- generated_from_trainer |
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metrics: |
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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: deberta-v3-large-finetuned-synthetic-paraphrase-only |
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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-synthetic-paraphrase-only |
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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: 0.0120 |
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- F1: 0.9768 |
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- Precision: 0.9961 |
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- Recall: 0.9583 |
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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: 6e-06 |
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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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- lr_scheduler_warmup_steps: 50 |
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- num_epochs: 3 |
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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 | F1 | Precision | Recall | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:---------:|:------:| |
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| 0.0086 | 1.0 | 10205 | 0.0114 | 0.9642 | 0.9846 | 0.9446 | |
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| 0.0059 | 2.0 | 20410 | 0.0143 | 0.9658 | 0.9961 | 0.9373 | |
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| 0.0 | 3.0 | 30615 | 0.0141 | 0.9716 | 0.9961 | 0.9483 | |
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### Framework versions |
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- Transformers 4.20.1 |
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- Pytorch 1.11.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.12.1 |
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