model weights, checkpoint 210000oapmc_twin_concat_pubmedbert_vicreg_contrast,

config.json

@@ -0,0 +1,45 @@
+{
+  "_name_or_path": "microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext",
+  "architectures": [
+    "Twin"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "keys_to_ignore_at_inference": [
+    "representations"
+  ],
+  "layer_norm_eps": 1e-12,
+  "loss_coeff": {
+    "contrast_loss": 1.0,
+    "cosine_loss": 1.0,
+    "cov_loss": 1.0,
+    "cov_xy_loss": 1.0,
+    "diag_xy_loss": 1.0,
+    "dot_loss": 1.0,
+    "mse_loss": 1.0,
+    "std_loss": 1.0
+  },
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "pretrained": "microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext",
+  "torch_dtype": "float32",
+  "transformers_version": "4.31.0",
+  "twin_loss": [
+    "dot_loss",
+    "cov_loss",
+    "std_loss",
+    "contrast_loss"
+  ],
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

pytorch_model.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:722eaa94546876ae2640be6abd80f2ca3ae0f9f008cae9598de4d8c41ebaea37
+size 438029033