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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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+ datasets:
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+ - boolq
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: deberta-v3-large_boolq
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+ results:
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+ - task:
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+ name: Text Classification
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+ type: text-classification
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+ dataset:
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+ name: boolq
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+ type: boolq
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+ config: default
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+ split: validation
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.882262996941896
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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_boolq
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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 boolq dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5796
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+ - Accuracy: 0.8823
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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: 1e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 64
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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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: 5.0
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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 | 0.85 | 250 | 0.3265 | 0.8740 |
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+ | 0.3786 | 1.69 | 500 | 0.3212 | 0.8844 |
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+ | 0.3786 | 2.54 | 750 | 0.4205 | 0.8838 |
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+ | 0.1324 | 3.39 | 1000 | 0.5393 | 0.8832 |
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+ | 0.1324 | 4.24 | 1250 | 0.5796 | 0.8823 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.32.1
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+ - Pytorch 2.0.1+cu117
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+ - Datasets 2.14.4
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+ - Tokenizers 0.13.3
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