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update model card README.md

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+ ---
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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-syndag-multiclass-not-bloom
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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-large-finetuned-syndag-multiclass-not-bloom
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+
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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: 0.0197
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+ - F1: 0.9956
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+ - Precision: 0.9956
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+ - Recall: 0.9956
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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: 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: 1
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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 | F1 | Precision | Recall |
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+ |:-------------:|:-----:|:-----:|:---------------:|:------:|:---------:|:------:|
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+ | 0.0194 | 1.0 | 10847 | 0.0222 | 0.9955 | 0.9955 | 0.9955 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.18.0
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+ - Pytorch 1.11.0
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+ - Datasets 2.1.0
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+ - Tokenizers 0.12.1