test manual upload to HF

config.json

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+{
+  "best_val_loss": Infinity,
+  "comet_ai_key": null,
+  "context_observations": {
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+    "past_time_ratio": 0.1,
+    "split_past_future": false,
+    "type": "pk_peak_half_life"
+  },
+  "debug_test": true,
+  "dosing": {
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+      2.0
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+      0.5
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+    "route_options": [
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+      "iv"
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+  "experiment_indentifier": null,
+  "experiment_name": "aicmepk",
+  "hf_model_card_path": [
+    "hf_model_cards",
+    "AICME-PK_Readme.md"
+  ],
+  "hf_model_name": "AICMEPK_cluster",
+  "hugging_face_token": null,
+  "meta_study": {
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+      5
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+      "Drug_B",
+      "Drug_C"
+    ],
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+    "time_start": 0.0,
+    "time_stop": 24.0
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+  "mix_data": {
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+    "keep_tempfile": false,
+    "log_transform": false,
+    "n_of_databatches": null,
+    "n_of_permutations": 3,
+    "n_of_target_individuals": 1,
+    "normalize_by_max": true,
+    "normalize_time": true,
+    "pretraining_epochs": 800,
+    "pretraining_protocol": "none",
+    "recreate_tempfile": false,
+    "split_seed": 42,
+    "split_strategy": "study",
+    "store_in_tempfile": false,
+    "tempfile_path": [
+      "preprocessed",
+      "simulated_ou_as_rates"
+    ],
+    "test_empirical_datasets": [
+      "cesarali/Indometacin"
+    ],
+    "test_protocol": "simulated",
+    "test_size": 64,
+    "tqdm_progress": false,
+    "train_size": 320,
+    "val_protocol": "simulated",
+    "val_size": 64,
+    "z_score_normalization": false
+  },
+  "model_type": "node_pk",
+  "my_results_path": null,
+  "name_str": "AICMEPK",
+  "network": {
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+    "aggregator_num_heads": 8,
+    "aggregator_type": "attention",
+    "combine_latent_mode": "mlp",
+    "cov_proj_dim": 16,
+    "decoder_attention_layers": 2,
+    "decoder_hidden_dim": 512,
+    "decoder_name": "TransformerDecoderZiQuery",
+    "decoder_num_layers": 4,
+    "decoder_rnn_hidden_dim": 256,
+    "drift_activation": "Tanh",
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+    "dropout": 0.1,
+    "encoder_rnn_hidden_dim": 256,
+    "exclusive_node_step": false,
+    "individual_encoder_name": "RNNContextEncoder",
+    "individual_encoder_number_of_heads": 4,
+    "init_hidden_num_layers": 4,
+    "input_encoding_hidden_dim": 128,
+    "kl_weight": 1.0,
+    "loss_name": "nll",
+    "node_step": true,
+    "norm": "layer",
+    "output_head_num_layers": 3,
+    "prediction_latent_deterministic": false,
+    "prediction_only": false,
+    "rnn_decoder_number_of_layers": 4,
+    "rnn_individual_encoder_number_of_layers": 4,
+    "study_latent_deterministic": false,
+    "time_obs_encoder_hidden_dim": 256,
+    "time_obs_encoder_output_dim": 256,
+    "use_attention": true,
+    "use_invariance_loss": true,
+    "use_kl_i": true,
+    "use_kl_i_np": true,
+    "use_kl_init": true,
+    "use_kl_s": true,
+    "use_self_attention": true,
+    "use_time_deltas": true,
+    "zi_latent_dim": 256
+  },
+  "run_index": 0,
+  "tags": [
+    "SIM_PRIOR",
+    "A-0"
+  ],
+  "target_observations": {
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+    "max_num_obs": 15,
+    "max_past": 5,
+    "min_past": 3,
+    "obs_dataset": "/home/ojedamarin/Projects/Pharma/generative_pk/data/preprocessed/lenuzza/Lenuzza2016.csv",
+    "past_time_ratio": 0.1,
+    "split_past_future": true,
+    "type": "pk_peak_half_life"
+  },
+  "train": {
+    "amsgrad": false,
+    "batch_size": 32,
+    "betas": [
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+      0.999
+    ],
+    "epochs": 100,
+    "eps": 1e-08,
+    "eval_empirical_every_pct": 0.5,
+    "gradient_clip_val": 1.0,
+    "learning_rate": 0.00023,
+    "log_image_every_epoch": 2,
+    "log_interval": 1,
+    "log_vcp": false,
+    "num_batch_plot": 1,
+    "num_workers": 8,
+    "optimizer_name": "AdamW",
+    "persistent_workers": true,
+    "scheduler_name": "CosineAnnealingLR",
+    "scheduler_params": {
+      "T_max": 1000,
+      "eta_min": 5e-05,
+      "last_epoch": -1
+    },
+    "shuffle_val": true,
+    "val_empirical_every_pct_epochs": 0.5,
+    "weight_decay": 0.0001
+  },
+  "transformers_version": "4.52.4",
+  "upload_to_hf_hub": false,
+  "verbose": false
+}

pytorch_model.bin

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