model weights, checkpoint 210000oapmc_twin_concat_pubmedbert_vicreg_contrast,

config.json

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+{
+ "_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