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deberta-v3-small-autextification-adapter

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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-small
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - autextification2023
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: deberta-v3-small-autextification-adapter
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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-small-autextification-adapter
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+
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+ This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the autextification2023 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6931
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+ - Accuracy: 0.4969
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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: 0.0001
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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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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 500
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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 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.6967 | 1.0 | 3808 | 0.6931 | 0.4969 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.0
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
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+ "lora_dropout": 0.05,
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+ "peft_type": "LORA",
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+ "r": 16,
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+ "target_modules": [
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+ "value_proj",
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+ "query_proj"
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+ ],
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+ "task_type": "SEQ_CLS"
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+ }
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