NeuronDS/CL_forecasting_foundation_model
09
1{2 "architectures": [3 "PatchTSMixerForPrediction"4 ],5 "channel_consistent_masking": true,6 "context_length": 336,7 "d_model": 16,8 "distribution_output": "student_t",9 "dropout": 0.2,10 "expansion_factor": 2,11 "gated_attn": true,12 "head_aggregation": "max_pool",13 "head_dropout": 0.2,14 "init_std": 0.02,15 "loss": "mse",16 "mask_type": "random",17 "mask_value": 0,18 "masked_loss": true,19 "mode": "common_channel",20 "model_type": "patchtsmixer",21 "norm_eps": 1e-05,22 "norm_mlp": "LayerNorm",23 "num_forecast_mask_patches": [24 225 ],26 "num_input_channels": 5,27 "num_layers": 8,28 "num_parallel_samples": 100,29 "num_patches": 42,30 "num_targets": 3,31 "output_range": null,32 "patch_last": true,33 "patch_length": 8,34 "patch_stride": 8,35 "positional_encoding_type": "sincos",36 "post_init": false,37 "prediction_channel_indices": null,38 "prediction_length": 24,39 "random_mask_ratio": 0.5,40 "scaling": "std",41 "self_attn": false,42 "self_attn_heads": 1,43 "torch_dtype": "float32",44 "transformers_version": "4.37.2",45 "unmasked_channel_indices": null,46 "use_positional_encoding": false47}48 