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README.md ADDED
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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-v3
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+ results: []
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+ ---
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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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+
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+ # deberta-v3-base-orgs-v3
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+
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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: 0.1182
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+ - Precision: 0.8008
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+ - Recall: 0.7751
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+ - F1: 0.7877
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+ - Accuracy: 0.9627
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 8e-05
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+ - train_batch_size: 256
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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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+ - lr_scheduler_warmup_steps: 20
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+ - num_epochs: 3.0
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.0526 | 1.4 | 600 | 0.1109 | 0.7917 | 0.7741 | 0.7828 | 0.9621 |
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+ | 0.0434 | 2.8 | 1200 | 0.1182 | 0.8008 | 0.7751 | 0.7877 | 0.9627 |
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+
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+
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+ ### Framework versions
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+
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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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