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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: checkpoints_28_9_microsoft_deberta_V2
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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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+ # checkpoints_28_9_microsoft_deberta_V2
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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: 0.5675
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+ - Map@3: 0.8842
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+ - Accuracy: 0.815
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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: 32
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+ - total_train_batch_size: 64
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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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+ | 1.0011 | 0.11 | 100 | 0.8842 | 0.8258 | 0.74 |
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+ | 0.8398 | 0.21 | 200 | 0.6978 | 0.8667 | 0.79 |
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+ | 0.8414 | 0.32 | 300 | 0.6337 | 0.8625 | 0.795 |
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+ | 0.7461 | 0.43 | 400 | 0.6609 | 0.8600 | 0.775 |
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+ | 0.7131 | 0.53 | 500 | 0.6329 | 0.8758 | 0.805 |
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+ | 0.6891 | 0.64 | 600 | 0.6157 | 0.8892 | 0.83 |
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+ | 0.6969 | 0.75 | 700 | 0.5917 | 0.8808 | 0.805 |
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+ | 0.6775 | 0.85 | 800 | 0.5698 | 0.8817 | 0.81 |
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+ | 0.6534 | 0.96 | 900 | 0.5675 | 0.8842 | 0.815 |
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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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