add model

.gitignore

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+checkpoint-*/

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model_index:
+  name: bert-base-uncased-finetuned-sst2-sst2-membership
+---
+
+<!-- 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. -->
+
+# bert-base-uncased-finetuned-sst2-sst2-membership
+
+This model is a fine-tuned version of [ikevin98/bert-base-uncased-finetuned-sst2](https://huggingface.co/ikevin98/bert-base-uncased-finetuned-sst2) on an unkown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0190
+- Accuracy: 0.2321
+
+## 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: 2e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.0234        | 1.0   | 3813 | 0.0190          | 0.2321   |
+
+
+### Framework versions
+
+- Transformers 4.9.2
+- Pytorch 1.8.1
+- Datasets 1.11.0
+- Tokenizers 0.10.1

config.json

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+{
+  "_name_or_path": "ikevin98/bert-base-uncased-finetuned-sst2",
+  "architectures": [
+    "MembershipBertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_length": 128,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "pretrained_model_name_or_path": "ikevin98/bert-base-uncased-finetuned-sst2",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.9.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

pytorch_model.bin

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special_tokens_map.json

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+{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}

tokenizer_config.json

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+{"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 512, "special_tokens_map_file": null, "name_or_path": "ikevin98/bert-base-uncased-finetuned-sst2", "max_length": 128, "padding": true, "tokenizer_class": "BertTokenizer"}

training_args.bin

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