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End of training

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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-large
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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-large-262-ver1
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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-262-ver1
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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: 0.0768
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+ - Precision: 0.9904
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+ - Recall: 0.9904
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+ - F1: 0.9904
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+ - Accuracy: 0.9904
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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: 2e-05
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+ - train_batch_size: 12
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+ - eval_batch_size: 12
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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: 5
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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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+ | 0.0624 | 1.0 | 1287 | 0.0447 | 0.9907 | 0.9907 | 0.9907 | 0.9907 |
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+ | 0.0272 | 2.0 | 2574 | 0.0899 | 0.9865 | 0.9865 | 0.9865 | 0.9865 |
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+ | 0.0136 | 3.0 | 3861 | 0.0605 | 0.9894 | 0.9894 | 0.9894 | 0.9894 |
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+ | 0.0071 | 4.0 | 5148 | 0.0771 | 0.9894 | 0.9894 | 0.9894 | 0.9894 |
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+ | 0.0015 | 5.0 | 6435 | 0.0768 | 0.9904 | 0.9904 | 0.9904 | 0.9904 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.0
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+ - Pytorch 2.2.0
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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+ "_name_or_path": "microsoft/deberta-v3-large",
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+ "hidden_dropout_prob": 0.1,
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