fine tuned ms-marco-MiniLM-L-6-v2 on twitter_sentiment_analysis for text classification task

config.json

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+{
+  "_name_or_path": "/content/drive/MyDrive/CyShield/Sentiment Analysis/ms-marco-MiniLM-L-6-v2/checkpoint-30000/",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 384,
+  "id2label": {
+    "0": "Negative",
+    "1": "Positive"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 1536,
+  "label2id": {
+    "Negative": 0,
+    "Positive": 1
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 6,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "sbert_ce_default_activation_function": "torch.nn.modules.linear.Identity",
+  "torch_dtype": "float32",
+  "transformers_version": "4.35.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
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+size 90867952