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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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+ model-index:
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+ - name: deberta-v3-large-math-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-math-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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+ - eval_loss: 0.1289
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+ - eval_precision: 0.9722
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+ - eval_recall: 0.9722
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+ - eval_f1: 0.9722
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+ - eval_accuracy: 0.9722
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+ - eval_runtime: 7.4496
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+ - eval_samples_per_second: 169.136
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+ - eval_steps_per_second: 14.095
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+ - epoch: 5.0
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+ - step: 2100
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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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+ ### Framework versions
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+
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+ - Transformers 4.39.3
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+ - Pytorch 2.1.2
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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+ {
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+ "_name_or_path": "microsoft/deberta-v3-large",
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+ "architectures": [
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+ "DebertaV2ForSequenceClassification"
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+ ],
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