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README.md

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+# DeBERTa-Large ASAP Essay Scoring Model
+
+This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) for automated essay scoring on the ASAP (Automated Student Assessment Prize) dataset, specifically trained on **Question 1**.
+
+## Model Description
+
+- **Model Type**: Sequence Classification
+- **Architecture**: DeBERTa-v3-Large (24 layers, 1024 hidden size, 16 attention heads)
+- **Task**: Automated Essay Scoring
+- **Language**: English
+- **Dataset**: ASAP Question 1
+- **Number of Classes**: 4 (score levels)
+
+## Dataset
+
+This model was trained on the ASAP (Automated Student Assessment Prize) dataset, specifically Question 1. The ASAP dataset contains student essays with human-scored ratings.
+
+- **Dataset Source**: [ASAP-SAS Kaggle Competition](https://www.kaggle.com/c/asap-sas/overview)
+- **Task**: Score student essays on a predefined rubric
+- **Question 1 Prompt**: The dataset contains essays written in response to specific prompts, with scores assigned by human raters
+
+## Training Details
+
+- **Base Model**: microsoft/deberta-v3-large
+- **Training Data**: ASAP dataset Question 1
+
+## License
+
+Please refer to the original DeBERTa-v3-large model license and the ASAP dataset terms of use. 

added_tokens.json

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config.json

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+{
+  "_name_or_path": "microsoft/deberta-v3-large",
+  "architectures": [
+    "DebertaV2ForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3"
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+  "intermediate_size": 4096,
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+    "LABEL_2": 2,
+    "LABEL_3": 3
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+  "layer_norm_eps": 1e-07,
+  "max_position_embeddings": 512,
+  "max_relative_positions": -1,
+  "model_type": "deberta-v2",
+  "norm_rel_ebd": "layer_norm",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "pad_token_id": 0,
+  "pooler_dropout": 0,
+  "pooler_hidden_act": "gelu",
+  "pooler_hidden_size": 1024,
+  "pos_att_type": [
+    "p2c",
+    "c2p"
+  ],
+  "position_biased_input": false,
+  "position_buckets": 256,
+  "relative_attention": true,
+  "share_att_key": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.26.0",
+  "type_vocab_size": 0,
+  "vocab_size": 128100
+}

pytorch_model.bin

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special_tokens_map.json

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spm.model

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tokenizer_config.json

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+{
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+  "do_lower_case": false,
+  "eos_token": "[SEP]",
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+  "model_max_length": 1000000000000000019884624838656,
+  "name_or_path": "microsoft/deberta-v3-large",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
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+  "split_by_punct": false,
+  "tokenizer_class": "DebertaV2Tokenizer",
+  "unk_token": "[UNK]",
+  "vocab_type": "spm"
+}