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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: 1_microsoft_deberta_V1.1
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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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+ # 1_microsoft_deberta_V1.1
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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: 0.7138
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+ - Map@3: 0.8492
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+ - Accuracy: 0.775
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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: 2
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+ - eval_batch_size: 4
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+ - seed: 42
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+ - gradient_accumulation_steps: 16
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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: cosine
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 1
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Map@3 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|
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+ | 1.6141 | 0.03 | 50 | 1.6087 | 0.6242 | 0.51 |
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+ | 1.336 | 0.05 | 100 | 1.1398 | 0.7550 | 0.645 |
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+ | 0.9441 | 0.08 | 150 | 0.8809 | 0.8150 | 0.7 |
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+ | 0.9279 | 0.11 | 200 | 0.7528 | 0.8383 | 0.73 |
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+ | 0.8639 | 0.13 | 250 | 0.7259 | 0.8525 | 0.76 |
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+ | 0.8255 | 0.16 | 300 | 0.7363 | 0.8592 | 0.785 |
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+ | 0.8411 | 0.19 | 350 | 0.7052 | 0.8483 | 0.76 |
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+ | 0.856 | 0.21 | 400 | 0.7097 | 0.8408 | 0.745 |
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+ | 0.7753 | 0.24 | 450 | 0.6860 | 0.8575 | 0.775 |
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+ | 0.7941 | 0.27 | 500 | 0.7146 | 0.8525 | 0.765 |
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+ | 0.8062 | 0.29 | 550 | 0.7138 | 0.8492 | 0.775 |
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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 2.0.0
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+ - Datasets 2.9.0
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+ - Tokenizers 0.13.3
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