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Classifier_with_external_sets_04

Text Classification
Transformers
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deberta-v2
Generated from Trainer
Inference Endpoints
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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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+ - accuracy
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+ model-index:
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+ - name: Classifier_with_external_sets_04
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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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+ # Classifier_with_external_sets_04
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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 the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2741
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+ - Accuracy: 0.9193
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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: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 32
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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: 26
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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 | Accuracy |
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+ |:-------------:|:-------:|:----:|:---------------:|:--------:|
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+ | No log | 0.9983 | 289 | 0.3540 | 0.8893 |
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+ | 0.5256 | 2.0 | 579 | 0.3874 | 0.8673 |
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+ | 0.5256 | 2.9983 | 868 | 0.3275 | 0.8991 |
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+ | 0.378 | 4.0 | 1158 | 0.3244 | 0.9028 |
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+ | 0.378 | 4.9983 | 1447 | 0.4013 | 0.8312 |
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+ | 0.4029 | 6.0 | 1737 | 0.4052 | 0.8428 |
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+ | 0.3932 | 6.9983 | 2026 | 0.3667 | 0.8801 |
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+ | 0.3932 | 8.0 | 2316 | 0.3972 | 0.8385 |
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+ | 0.3972 | 8.9983 | 2605 | 0.3983 | 0.8648 |
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+ | 0.3972 | 10.0 | 2895 | 0.3805 | 0.8587 |
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+ | 0.3734 | 10.9983 | 3184 | 0.3735 | 0.8746 |
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+ | 0.3734 | 12.0 | 3474 | 0.3256 | 0.8893 |
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+ | 0.3752 | 12.9983 | 3763 | 0.2800 | 0.9101 |
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+ | 0.3169 | 14.0 | 4053 | 0.3071 | 0.8979 |
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+ | 0.3169 | 14.9983 | 4342 | 0.3083 | 0.9052 |
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+ | 0.312 | 16.0 | 4632 | 0.2894 | 0.9168 |
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+ | 0.312 | 16.9983 | 4921 | 0.3725 | 0.8624 |
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+ | 0.3162 | 18.0 | 5211 | 0.3163 | 0.8979 |
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+ | 0.3185 | 18.9983 | 5500 | 0.3030 | 0.8991 |
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+ | 0.3185 | 20.0 | 5790 | 0.3045 | 0.8997 |
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+ | 0.2951 | 20.9983 | 6079 | 0.2944 | 0.9076 |
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+ | 0.2951 | 22.0 | 6369 | 0.2693 | 0.9199 |
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+ | 0.2916 | 22.9983 | 6658 | 0.2711 | 0.9187 |
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+ | 0.2916 | 24.0 | 6948 | 0.2651 | 0.9211 |
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+ | 0.2593 | 24.9983 | 7237 | 0.2696 | 0.9193 |
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+ | 0.2646 | 25.9551 | 7514 | 0.2741 | 0.9193 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.0
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+ - Pytorch 2.2.2+cu121
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+ - Datasets 2.19.0
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+ - Tokenizers 0.19.1
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