Upload fine-tuned RoBERTa model

README.md

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+---
+library_name: transformers
+license: mit
+base_model: Yuvrajg2107/deberta-v3-hybrid-detector_12
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: deberta-v3-hybrid-detector_v2_universal
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# deberta-v3-hybrid-detector_v2_universal
+
+This model is a fine-tuned version of [Yuvrajg2107/deberta-v3-hybrid-detector_12](https://huggingface.co/Yuvrajg2107/deberta-v3-hybrid-detector_12) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0389
+- Accuracy: 0.9631
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-06
+- train_batch_size: 8
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 32
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 1
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| 0.0127        | 0.1455 | 1000 | 0.0275          | 0.9659   |
+| 0.0083        | 0.2909 | 2000 | 0.0469          | 0.9541   |
+| 0.0065        | 0.4364 | 3000 | 0.0439          | 0.9544   |
+| 0.0063        | 0.5818 | 4000 | 0.0207          | 0.9785   |
+| 0.007         | 0.7273 | 5000 | 0.0342          | 0.9647   |
+| 0.0046        | 0.8727 | 6000 | 0.0389          | 0.9631   |
+
+
+### Framework versions
+
+- Transformers 4.57.3
+- Pytorch 2.6.0+cu124
+- Datasets 4.4.2
+- Tokenizers 0.22.1

added_tokens.json

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+{
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+}

config.json

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+{
+  "architectures": [
+    "DebertaV2ForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 1,
+  "dtype": "float32",
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-07,
+  "legacy": true,
+  "max_position_embeddings": 512,
+  "max_relative_positions": -1,
+  "model_type": "deberta-v2",
+  "norm_rel_ebd": "layer_norm",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 6,
+  "pad_token_id": 0,
+  "pooler_dropout": 0,
+  "pooler_hidden_act": "gelu",
+  "pooler_hidden_size": 768,
+  "pos_att_type": [
+    "p2c",
+    "c2p"
+  ],
+  "position_biased_input": false,
+  "position_buckets": 256,
+  "relative_attention": true,
+  "share_att_key": true,
+  "transformers_version": "4.57.3",
+  "type_vocab_size": 0,
+  "vocab_size": 128100
+}

model.safetensors

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special_tokens_map.json

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+    "lstrip": false,
+    "normalized": true,
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+}

spm.model

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tokenizer_config.json

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+  "cls_token": "[CLS]",
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+  "mask_token": "[MASK]",
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+  "pad_token": "[PAD]",
+  "pad_token_type_id": 0,
+  "padding_side": "right",
+  "sep_token": "[SEP]",
+  "sp_model_kwargs": {},
+  "split_by_punct": false,
+  "stride": 0,
+  "tokenizer_class": "DebertaV2Tokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": "[UNK]",
+  "vocab_type": "spm"
+}

training_args.bin

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