Upload folder using huggingface_hub
Browse files- outputs/pep-affibody-ablation-fe/libB_pseudo_bf16/best_model.pt +3 -0
- outputs/pep-affibody-ablation-fe/libB_pseudo_bf16/config.json +262 -0
- outputs/pep-affibody-ablation-fe/libB_pseudo_bf16/last_model.pt +3 -0
- outputs/pep-affibody-ablation-fe/libB_pseudo_bf16/metrics.csv +0 -0
- outputs/pep-affibody-ablation-fe/libB_pseudo_bf16/metrics.json +0 -0
- outputs/pep-affibody-ablation-fe/libB_pseudo_bf16/summary.txt +407 -0
- outputs/pep-affibody-ablation-fe/libB_pseudo_bf16/train.log +0 -0
outputs/pep-affibody-ablation-fe/libB_pseudo_bf16/best_model.pt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:0d72b5aa5573b04611dde1bdb3c2815337b4ca3938b3e9077ae65267e3b67f1e
|
| 3 |
+
size 3261776405
|
outputs/pep-affibody-ablation-fe/libB_pseudo_bf16/config.json
ADDED
|
@@ -0,0 +1,262 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"args": {
|
| 3 |
+
"config_path": "data/esm2_t33_650M_UR50D.json",
|
| 4 |
+
"checkpoint_path": "mint.ckpt",
|
| 5 |
+
"train_csv": "data/libB/train_fold_enrichment_freqmean_pseudo_1to1.csv",
|
| 6 |
+
"val_csv": [
|
| 7 |
+
"data/libB/val_fold_enrichment_freqmean_pseudo_1to1.csv",
|
| 8 |
+
"data/libB/val_fold_enrichment_freqmean_pseudo_1to1_v2.csv"
|
| 9 |
+
],
|
| 10 |
+
"best_val_index": 0,
|
| 11 |
+
"train_limit": null,
|
| 12 |
+
"log_transform": true,
|
| 13 |
+
"use_multimer": true,
|
| 14 |
+
"unfreeze_last_n": 5,
|
| 15 |
+
"sep_chains": true,
|
| 16 |
+
"hidden_dim": 512,
|
| 17 |
+
"dropout": 0.2,
|
| 18 |
+
"bs": 256,
|
| 19 |
+
"num_epochs": 10,
|
| 20 |
+
"lr": 0.001,
|
| 21 |
+
"backbone_lr": 0.0001,
|
| 22 |
+
"loss_fn": "mse",
|
| 23 |
+
"huber_delta": 1.0,
|
| 24 |
+
"truncation_rate": 0.0,
|
| 25 |
+
"truncation_warmup_steps": 3000,
|
| 26 |
+
"consistency_col": null,
|
| 27 |
+
"truncation_consistency_bonus": 0.5,
|
| 28 |
+
"grad_clip": 1.0,
|
| 29 |
+
"val_interval": 100,
|
| 30 |
+
"mixed_precision": "bf16",
|
| 31 |
+
"gradient_accumulation_steps": 2,
|
| 32 |
+
"activation_checkpointing": false,
|
| 33 |
+
"lr_scheduler_type": "constant",
|
| 34 |
+
"warmup_steps": 0,
|
| 35 |
+
"lr_min": 0.0,
|
| 36 |
+
"lr_scheduler_kwargs": "{}",
|
| 37 |
+
"sample_weight_col": null,
|
| 38 |
+
"negative_weight": 1.0,
|
| 39 |
+
"use_binding_quality": false,
|
| 40 |
+
"bq_w_count": 0.7,
|
| 41 |
+
"bq_w_fe": 0.3,
|
| 42 |
+
"no_wandb": false,
|
| 43 |
+
"wandb_project": "pep-affibody-ablation-fe",
|
| 44 |
+
"wandb_entity": "protein_llm",
|
| 45 |
+
"wandb_run_name": "libB_pseudo_bf16",
|
| 46 |
+
"output_dir": "/home/pj25000082/ku50001421/mint/outputs/pep-affibody-ablation-fe/libB_pseudo_bf16",
|
| 47 |
+
"seed": 42,
|
| 48 |
+
"num_workers": 4,
|
| 49 |
+
"prefetch_factor": 2,
|
| 50 |
+
"device": "cuda"
|
| 51 |
+
},
|
| 52 |
+
"model_cfg": {
|
| 53 |
+
"no_progress_bar": false,
|
| 54 |
+
"log_interval": 100,
|
| 55 |
+
"log_format": "json",
|
| 56 |
+
"azureml_logging": false,
|
| 57 |
+
"seed": 1,
|
| 58 |
+
"cpu": false,
|
| 59 |
+
"tpu": false,
|
| 60 |
+
"bf16": false,
|
| 61 |
+
"memory_efficient_bf16": false,
|
| 62 |
+
"fp16": true,
|
| 63 |
+
"memory_efficient_fp16": false,
|
| 64 |
+
"fp16_no_flatten_grads": false,
|
| 65 |
+
"fp16_init_scale": 4,
|
| 66 |
+
"fp16_scale_tolerance": 0.0,
|
| 67 |
+
"on_cpu_convert_precision": false,
|
| 68 |
+
"min_loss_scale": 0.0001,
|
| 69 |
+
"amp": false,
|
| 70 |
+
"amp_batch_retries": 2,
|
| 71 |
+
"amp_init_scale": 128,
|
| 72 |
+
"empty_cache_freq": 0,
|
| 73 |
+
"all_gather_list_size": 16384,
|
| 74 |
+
"model_parallel_size": 1,
|
| 75 |
+
"profile": false,
|
| 76 |
+
"reset_logging": false,
|
| 77 |
+
"suppress_crashes": false,
|
| 78 |
+
"use_plasma_view": false,
|
| 79 |
+
"plasma_path": "/tmp/plasma",
|
| 80 |
+
"criterion": "masked_lm",
|
| 81 |
+
"optimizer": "adam",
|
| 82 |
+
"lr_scheduler": "polynomial_decay",
|
| 83 |
+
"scoring": "bleu",
|
| 84 |
+
"task": "p_masked_lm_cluster_resample",
|
| 85 |
+
"num_workers": 0,
|
| 86 |
+
"skip_invalid_size_inputs_valid_test": true,
|
| 87 |
+
"max_tokens": 1024,
|
| 88 |
+
"required_batch_size_multiple": 8,
|
| 89 |
+
"required_seq_len_multiple": 1,
|
| 90 |
+
"dataset_impl": "fasta",
|
| 91 |
+
"data_buffer_size": 10,
|
| 92 |
+
"train_subset": "train50",
|
| 93 |
+
"valid_subset": "valid50",
|
| 94 |
+
"ignore_unused_valid_subsets": true,
|
| 95 |
+
"validate_interval": 99999,
|
| 96 |
+
"validate_interval_updates": 0,
|
| 97 |
+
"validate_after_updates": 0,
|
| 98 |
+
"disable_validation": false,
|
| 99 |
+
"max_tokens_valid": 1024,
|
| 100 |
+
"curriculum": 0,
|
| 101 |
+
"gen_subset": "test",
|
| 102 |
+
"num_shards": 1,
|
| 103 |
+
"shard_id": 0,
|
| 104 |
+
"distributed_world_size": 512,
|
| 105 |
+
"distributed_num_procs": 8,
|
| 106 |
+
"distributed_rank": 0,
|
| 107 |
+
"distributed_backend": "nccl",
|
| 108 |
+
"distributed_port": 14490,
|
| 109 |
+
"device_id": 0,
|
| 110 |
+
"distributed_no_spawn": false,
|
| 111 |
+
"ddp_backend": "c10d",
|
| 112 |
+
"ddp_comm_hook": "none",
|
| 113 |
+
"bucket_cap_mb": 25,
|
| 114 |
+
"fix_batches_to_gpus": false,
|
| 115 |
+
"find_unused_parameters": false,
|
| 116 |
+
"fast_stat_sync": false,
|
| 117 |
+
"heartbeat_timeout": 3600,
|
| 118 |
+
"broadcast_buffers": false,
|
| 119 |
+
"slowmo_algorithm": "LocalSGD",
|
| 120 |
+
"localsgd_frequency": 3,
|
| 121 |
+
"nprocs_per_node": 8,
|
| 122 |
+
"pipeline_model_parallel": false,
|
| 123 |
+
"pipeline_chunks": 0,
|
| 124 |
+
"pipeline_checkpoint": "never",
|
| 125 |
+
"zero_sharding": "none",
|
| 126 |
+
"no_reshard_after_forward": false,
|
| 127 |
+
"fp32_reduce_scatter": false,
|
| 128 |
+
"cpu_offload": false,
|
| 129 |
+
"use_sharded_state": false,
|
| 130 |
+
"arch": "p_roberta_large",
|
| 131 |
+
"max_epoch": 500,
|
| 132 |
+
"max_update": 0,
|
| 133 |
+
"stop_time_hours": 0,
|
| 134 |
+
"clip_norm": 0.0,
|
| 135 |
+
"use_inf_norm": false,
|
| 136 |
+
"sentence_avg": false,
|
| 137 |
+
"update_freq": [
|
| 138 |
+
4
|
| 139 |
+
],
|
| 140 |
+
"lr": [
|
| 141 |
+
0.0004
|
| 142 |
+
],
|
| 143 |
+
"stop_min_lr": -1.0,
|
| 144 |
+
"use_bmuf": false,
|
| 145 |
+
"save_dir": "/fsx-protein/halilakin/checkpoints/33layer_lr_poly.sample_ur50_to_90.ngpu512",
|
| 146 |
+
"restore_file": "checkpoint_last.pt",
|
| 147 |
+
"reset_dataloader": false,
|
| 148 |
+
"reset_lr_scheduler": false,
|
| 149 |
+
"reset_meters": false,
|
| 150 |
+
"reset_optimizer": false,
|
| 151 |
+
"optimizer_overrides": "{}",
|
| 152 |
+
"save_interval": 99999,
|
| 153 |
+
"save_interval_updates": 10000,
|
| 154 |
+
"keep_interval_updates": -1,
|
| 155 |
+
"keep_interval_updates_pattern": -1,
|
| 156 |
+
"keep_last_epochs": -1,
|
| 157 |
+
"keep_best_checkpoints": -1,
|
| 158 |
+
"no_save": false,
|
| 159 |
+
"no_epoch_checkpoints": true,
|
| 160 |
+
"no_last_checkpoints": false,
|
| 161 |
+
"no_save_optimizer_state": false,
|
| 162 |
+
"best_checkpoint_metric": "loss",
|
| 163 |
+
"maximize_best_checkpoint_metric": false,
|
| 164 |
+
"patience": -1,
|
| 165 |
+
"checkpoint_suffix": "",
|
| 166 |
+
"checkpoint_shard_count": 1,
|
| 167 |
+
"load_checkpoint_on_all_dp_ranks": false,
|
| 168 |
+
"write_checkpoints_asynchronously": false,
|
| 169 |
+
"no_mid_epoch_validate": false,
|
| 170 |
+
"encoder_layerdrop": 0,
|
| 171 |
+
"quant_noise_pq": 0,
|
| 172 |
+
"quant_noise_pq_block_size": 8,
|
| 173 |
+
"quant_noise_scalar": 0,
|
| 174 |
+
"min_params_to_wrap": 100000000,
|
| 175 |
+
"data": "/fsx-protein/zhongkai/datasets/202104esm2/03_output",
|
| 176 |
+
"sample_break_mode": "eos",
|
| 177 |
+
"tokens_per_sample": 1024,
|
| 178 |
+
"mask_prob": 0.15,
|
| 179 |
+
"leave_unmasked_prob": 0.1,
|
| 180 |
+
"random_token_prob": 0.1,
|
| 181 |
+
"freq_weighted_replacement": false,
|
| 182 |
+
"mask_whole_words": false,
|
| 183 |
+
"mask_multiple_length": 1,
|
| 184 |
+
"mask_stdev": 0.0,
|
| 185 |
+
"shorten_method": "random_crop",
|
| 186 |
+
"shorten_data_split_list": "train50",
|
| 187 |
+
"num_batch_buckets": 0,
|
| 188 |
+
"cluster_resample_fasta_path": "/fsx-protein/zhongkai/datasets/202104esm2/03_output/uniref90.filtered.fasta",
|
| 189 |
+
"cluster_resample_seq_id": 90,
|
| 190 |
+
"cluster_resample_ur50_ur90_ur100_path": "/fsx-protein/zhongkai/datasets/202104esm2/01_inputs/ur50_ur90_ur100.no_ur_id_prefix.csv",
|
| 191 |
+
"adam_betas": "[0.9,0.98]",
|
| 192 |
+
"adam_eps": 1e-08,
|
| 193 |
+
"weight_decay": 0.01,
|
| 194 |
+
"use_old_adam": false,
|
| 195 |
+
"warmup_updates": 2000,
|
| 196 |
+
"end_learning_rate": 2e-05,
|
| 197 |
+
"power": 1.0,
|
| 198 |
+
"total_num_update": "450000",
|
| 199 |
+
"pad": 1,
|
| 200 |
+
"eos": 2,
|
| 201 |
+
"unk": 3,
|
| 202 |
+
"max_positions": 1024,
|
| 203 |
+
"activation_fn": "gelu",
|
| 204 |
+
"use_rotary_embeddings": true,
|
| 205 |
+
"encoder_normalize_after": true,
|
| 206 |
+
"preact_normalize": true,
|
| 207 |
+
"token_dropout": true,
|
| 208 |
+
"layer_norm_fp32": true,
|
| 209 |
+
"attention_dropout": 0.0,
|
| 210 |
+
"dropout": 0.0,
|
| 211 |
+
"activation_dropout": 0.0,
|
| 212 |
+
"encoder_attention_heads": 20,
|
| 213 |
+
"encoder_embed_dim": 1280,
|
| 214 |
+
"encoder_ffn_embed_dim": 5120,
|
| 215 |
+
"encoder_layers": 33,
|
| 216 |
+
"no_seed_provided": false,
|
| 217 |
+
"pooler_activation_fn": "tanh",
|
| 218 |
+
"pooler_dropout": 0.0,
|
| 219 |
+
"encoder_normalize_before": false,
|
| 220 |
+
"encoder_learned_pos": false,
|
| 221 |
+
"use_bert_init": false,
|
| 222 |
+
"checkpoint_transformer_block": false,
|
| 223 |
+
"checkpoint_activations": false,
|
| 224 |
+
"effective_attention": false,
|
| 225 |
+
"_name": "p_roberta_large",
|
| 226 |
+
"untie_weights_roberta": false
|
| 227 |
+
},
|
| 228 |
+
"environment": {
|
| 229 |
+
"python_version": "3.10.19 (main, Oct 21 2025, 16:43:05) [GCC 11.2.0]",
|
| 230 |
+
"torch_version": "2.10.0+cu128",
|
| 231 |
+
"cuda_available": true,
|
| 232 |
+
"cuda_device": "NVIDIA H100 80GB HBM3",
|
| 233 |
+
"wandb_available": true
|
| 234 |
+
},
|
| 235 |
+
"git": {
|
| 236 |
+
"git_commit": "unknown",
|
| 237 |
+
"git_dirty": null
|
| 238 |
+
},
|
| 239 |
+
"timestamp": "2026-02-15 19:29:35",
|
| 240 |
+
"dataset": {
|
| 241 |
+
"train_csv": "data/libB/train_fold_enrichment_freqmean_pseudo_1to1.csv",
|
| 242 |
+
"val_csv": [
|
| 243 |
+
"data/libB/val_fold_enrichment_freqmean_pseudo_1to1.csv",
|
| 244 |
+
"data/libB/val_fold_enrichment_freqmean_pseudo_1to1_v2.csv"
|
| 245 |
+
],
|
| 246 |
+
"train_size": 1481332,
|
| 247 |
+
"train_positive_ratio": 0.5,
|
| 248 |
+
"train_count_mean": 2.6410122781388643,
|
| 249 |
+
"train_count_std": 16.249330698762655,
|
| 250 |
+
"train_count_max": 17196.0,
|
| 251 |
+
"val_0_csv": "data/libB/val_fold_enrichment_freqmean_pseudo_1to1.csv",
|
| 252 |
+
"val_0_size": 176,
|
| 253 |
+
"val_0_positive_ratio": 0.7670454545454546,
|
| 254 |
+
"val_0_count_mean": 84.94886363636364,
|
| 255 |
+
"val_0_count_std": 426.4907605080106,
|
| 256 |
+
"val_1_csv": "data/libB/val_fold_enrichment_freqmean_pseudo_1to1_v2.csv",
|
| 257 |
+
"val_1_size": 165,
|
| 258 |
+
"val_1_positive_ratio": 0.806060606060606,
|
| 259 |
+
"val_1_count_mean": 77.43636363636364,
|
| 260 |
+
"val_1_count_std": 427.8391721268735
|
| 261 |
+
}
|
| 262 |
+
}
|
outputs/pep-affibody-ablation-fe/libB_pseudo_bf16/last_model.pt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:5efd660a2b0ecdf5baed0e1bcf2f8295ade391911f2e7db97d14df8c9facaf4e
|
| 3 |
+
size 7524953661
|
outputs/pep-affibody-ablation-fe/libB_pseudo_bf16/metrics.csv
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
outputs/pep-affibody-ablation-fe/libB_pseudo_bf16/metrics.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
outputs/pep-affibody-ablation-fe/libB_pseudo_bf16/summary.txt
ADDED
|
@@ -0,0 +1,407 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
============================================================
|
| 2 |
+
Experiment Summary
|
| 3 |
+
============================================================
|
| 4 |
+
|
| 5 |
+
Output dir: /home/pj25000082/ku50001421/mint/outputs/pep-affibody-ablation-fe/libB_pseudo_bf16
|
| 6 |
+
Timestamp: 2026-02-16 18:48:31
|
| 7 |
+
Duration: 83951.4 seconds (1399.2 minutes)
|
| 8 |
+
|
| 9 |
+
--- Key Hyperparameters ---
|
| 10 |
+
lr: 0.001
|
| 11 |
+
backbone_lr: 0.0001
|
| 12 |
+
bs: 256
|
| 13 |
+
num_epochs: 10
|
| 14 |
+
unfreeze_last_n: 5
|
| 15 |
+
hidden_dim: 512
|
| 16 |
+
dropout: 0.2
|
| 17 |
+
log_transform: True
|
| 18 |
+
sep_chains: True
|
| 19 |
+
loss_fn: mse
|
| 20 |
+
huber_delta: 1.0
|
| 21 |
+
truncation_rate: 0.0
|
| 22 |
+
truncation_warmup_steps: 3000
|
| 23 |
+
truncation_consistency_bonus: 0.5
|
| 24 |
+
val_interval: 100
|
| 25 |
+
grad_clip: 1.0
|
| 26 |
+
seed: 42
|
| 27 |
+
mixed_precision: bf16
|
| 28 |
+
gradient_accumulation_steps: 2
|
| 29 |
+
lr_scheduler_type: constant
|
| 30 |
+
warmup_steps: 0
|
| 31 |
+
lr_min: 0.0
|
| 32 |
+
lr_scheduler_kwargs: {}
|
| 33 |
+
activation_checkpointing: False
|
| 34 |
+
num_workers: 4
|
| 35 |
+
prefetch_factor: 2
|
| 36 |
+
negative_weight: 1.0
|
| 37 |
+
use_binding_quality: False
|
| 38 |
+
bq_w_count: 0.7
|
| 39 |
+
bq_w_fe: 0.3
|
| 40 |
+
|
| 41 |
+
--- Best Validation Metrics ---
|
| 42 |
+
val_0_cs0_kendall: 0.2156
|
| 43 |
+
val_0_cs0_n: 60
|
| 44 |
+
val_0_cs0_pearson: 0.21365348994731903
|
| 45 |
+
val_0_cs0_r2: -4.1103
|
| 46 |
+
val_0_cs0_rmse: 0.9724
|
| 47 |
+
val_0_cs0_spearman: 0.2781
|
| 48 |
+
val_0_cs1_kendall: 0.3810
|
| 49 |
+
val_0_cs1_n: 14
|
| 50 |
+
val_0_cs1_pearson: 0.6624651551246643
|
| 51 |
+
val_0_cs1_r2: -0.4791
|
| 52 |
+
val_0_cs1_rmse: 0.5618
|
| 53 |
+
val_0_cs1_spearman: 0.4532
|
| 54 |
+
val_0_cs2_kendall: 0.5490
|
| 55 |
+
val_0_cs2_n: 14
|
| 56 |
+
val_0_cs2_pearson: 0.8056180477142334
|
| 57 |
+
val_0_cs2_r2: 0.4388
|
| 58 |
+
val_0_cs2_rmse: 0.9954
|
| 59 |
+
val_0_cs2_spearman: 0.6675
|
| 60 |
+
val_0_cs3_kendall: 0.6030
|
| 61 |
+
val_0_cs3_n: 88
|
| 62 |
+
val_0_cs3_pearson: 0.6629645824432373
|
| 63 |
+
val_0_cs3_r2: 0.1671
|
| 64 |
+
val_0_cs3_rmse: 1.3475
|
| 65 |
+
val_0_cs3_spearman: 0.7335
|
| 66 |
+
val_0_kendall: 0.7003
|
| 67 |
+
val_0_pearson: 0.8241990208625793
|
| 68 |
+
val_0_pr_auc: 0.9677
|
| 69 |
+
val_0_r2: 0.6435
|
| 70 |
+
val_0_r2_orig: -0.0026
|
| 71 |
+
val_0_rmse: 1.1551
|
| 72 |
+
val_0_rmse_orig: 425.8286
|
| 73 |
+
val_0_roc_auc: 0.8944
|
| 74 |
+
val_0_spearman: 0.8574
|
| 75 |
+
val_0_top20_precision: 1.0000
|
| 76 |
+
val_0_top50_precision: 1.0000
|
| 77 |
+
val_1_cs0_kendall: 0.1705
|
| 78 |
+
val_1_cs0_n: 56
|
| 79 |
+
val_1_cs0_pearson: 0.1607104390859604
|
| 80 |
+
val_1_cs0_r2: -4.2089
|
| 81 |
+
val_1_cs0_rmse: 1.0479
|
| 82 |
+
val_1_cs0_spearman: 0.2263
|
| 83 |
+
val_1_cs1_kendall: 0.3552
|
| 84 |
+
val_1_cs1_n: 19
|
| 85 |
+
val_1_cs1_pearson: 0.7219028472900391
|
| 86 |
+
val_1_cs1_r2: -1.4061
|
| 87 |
+
val_1_cs1_rmse: 0.6211
|
| 88 |
+
val_1_cs1_spearman: 0.4364
|
| 89 |
+
val_1_cs2_kendall: 0.6250
|
| 90 |
+
val_1_cs2_n: 12
|
| 91 |
+
val_1_cs2_pearson: 0.8879897594451904
|
| 92 |
+
val_1_cs2_r2: 0.6522
|
| 93 |
+
val_1_cs2_rmse: 0.8304
|
| 94 |
+
val_1_cs2_spearman: 0.7666
|
| 95 |
+
val_1_cs3_kendall: 0.6641
|
| 96 |
+
val_1_cs3_n: 78
|
| 97 |
+
val_1_cs3_pearson: 0.7661534547805786
|
| 98 |
+
val_1_cs3_r2: 0.4029
|
| 99 |
+
val_1_cs3_rmse: 1.2134
|
| 100 |
+
val_1_cs3_spearman: 0.8095
|
| 101 |
+
val_1_kendall: 0.6468
|
| 102 |
+
val_1_pearson: 0.8435776829719543
|
| 103 |
+
val_1_pr_auc: 0.9530
|
| 104 |
+
val_1_r2: 0.6715
|
| 105 |
+
val_1_r2_orig: 0.0056
|
| 106 |
+
val_1_rmse: 1.0785
|
| 107 |
+
val_1_rmse_orig: 425.3369
|
| 108 |
+
val_1_roc_auc: 0.8253
|
| 109 |
+
val_1_spearman: 0.8048
|
| 110 |
+
val_1_top20_precision: 1.0000
|
| 111 |
+
val_1_top50_precision: 1.0000
|
| 112 |
+
|
| 113 |
+
--- Best Test Metrics ---
|
| 114 |
+
|
| 115 |
+
--- Training History (val_spearman) ---
|
| 116 |
+
step 100 (epoch 1): val_spearman=0.4002 train_loss=0.4755
|
| 117 |
+
step 200 (epoch 1): val_spearman=0.3998 train_loss=0.3835
|
| 118 |
+
step 300 (epoch 1): val_spearman=0.3618 train_loss=0.3674
|
| 119 |
+
step 400 (epoch 1): val_spearman=0.4301 train_loss=0.3556
|
| 120 |
+
step 500 (epoch 1): val_spearman=0.5208 train_loss=0.3525
|
| 121 |
+
step 600 (epoch 1): val_spearman=0.5011 train_loss=0.3524
|
| 122 |
+
step 700 (epoch 1): val_spearman=0.5102 train_loss=0.3553
|
| 123 |
+
step 800 (epoch 1): val_spearman=0.5923 train_loss=0.3336
|
| 124 |
+
step 900 (epoch 1): val_spearman=0.5592 train_loss=0.3499
|
| 125 |
+
step 1000 (epoch 1): val_spearman=0.6022 train_loss=0.3309
|
| 126 |
+
step 1100 (epoch 1): val_spearman=0.6729 train_loss=0.3378
|
| 127 |
+
step 1200 (epoch 1): val_spearman=0.6790 train_loss=0.3366
|
| 128 |
+
step 1300 (epoch 1): val_spearman=0.6750 train_loss=0.3252
|
| 129 |
+
step 1400 (epoch 1): val_spearman=0.7067 train_loss=0.3283
|
| 130 |
+
step 1500 (epoch 1): val_spearman=0.6072 train_loss=0.3320
|
| 131 |
+
step 1600 (epoch 1): val_spearman=0.6993 train_loss=0.3289
|
| 132 |
+
step 1700 (epoch 1): val_spearman=0.6476 train_loss=0.3312
|
| 133 |
+
step 1800 (epoch 1): val_spearman=0.6780 train_loss=0.3237
|
| 134 |
+
step 1900 (epoch 1): val_spearman=0.6616 train_loss=0.3295
|
| 135 |
+
step 2000 (epoch 1): val_spearman=0.6771 train_loss=0.3270
|
| 136 |
+
step 2100 (epoch 1): val_spearman=0.7104 train_loss=0.3328
|
| 137 |
+
step 2200 (epoch 1): val_spearman=0.6848 train_loss=0.3235
|
| 138 |
+
step 2300 (epoch 1): val_spearman=0.7076 train_loss=0.3243
|
| 139 |
+
step 2400 (epoch 1): val_spearman=0.6631 train_loss=0.3258
|
| 140 |
+
step 2500 (epoch 1): val_spearman=0.7335 train_loss=0.3313
|
| 141 |
+
step 2600 (epoch 1): val_spearman=0.7135 train_loss=0.3256
|
| 142 |
+
step 2700 (epoch 1): val_spearman=0.7599 train_loss=0.3250
|
| 143 |
+
step 2800 (epoch 1): val_spearman=0.7327 train_loss=0.3251
|
| 144 |
+
step 2900 (epoch 2): val_spearman=0.7286 train_loss=0.3280
|
| 145 |
+
step 3000 (epoch 2): val_spearman=0.7045 train_loss=0.3226
|
| 146 |
+
step 3100 (epoch 2): val_spearman=0.7314 train_loss=0.3182
|
| 147 |
+
step 3200 (epoch 2): val_spearman=0.7498 train_loss=0.3126
|
| 148 |
+
step 3300 (epoch 2): val_spearman=0.7618 train_loss=0.3178
|
| 149 |
+
step 3400 (epoch 2): val_spearman=0.7497 train_loss=0.3211
|
| 150 |
+
step 3500 (epoch 2): val_spearman=0.7116 train_loss=0.3228
|
| 151 |
+
step 3600 (epoch 2): val_spearman=0.7906 train_loss=0.3160
|
| 152 |
+
step 3700 (epoch 2): val_spearman=0.7276 train_loss=0.3146
|
| 153 |
+
step 3800 (epoch 2): val_spearman=0.7192 train_loss=0.3203
|
| 154 |
+
step 3900 (epoch 2): val_spearman=0.7611 train_loss=0.3152
|
| 155 |
+
step 4000 (epoch 2): val_spearman=0.7465 train_loss=0.3132
|
| 156 |
+
step 4100 (epoch 2): val_spearman=0.7588 train_loss=0.3167
|
| 157 |
+
step 4200 (epoch 2): val_spearman=0.7728 train_loss=0.3180
|
| 158 |
+
step 4300 (epoch 2): val_spearman=0.7827 train_loss=0.3137
|
| 159 |
+
step 4400 (epoch 2): val_spearman=0.7532 train_loss=0.3171
|
| 160 |
+
step 4500 (epoch 2): val_spearman=0.7677 train_loss=0.3173
|
| 161 |
+
step 4600 (epoch 2): val_spearman=0.7805 train_loss=0.3223
|
| 162 |
+
step 4700 (epoch 2): val_spearman=0.7669 train_loss=0.3137
|
| 163 |
+
step 4800 (epoch 2): val_spearman=0.7809 train_loss=0.3150
|
| 164 |
+
step 4900 (epoch 2): val_spearman=0.7627 train_loss=0.3196
|
| 165 |
+
step 5000 (epoch 2): val_spearman=0.7679 train_loss=0.3153
|
| 166 |
+
step 5100 (epoch 2): val_spearman=0.7821 train_loss=0.3182
|
| 167 |
+
step 5200 (epoch 2): val_spearman=0.7567 train_loss=0.3119
|
| 168 |
+
step 5300 (epoch 2): val_spearman=0.7915 train_loss=0.3161
|
| 169 |
+
step 5400 (epoch 2): val_spearman=0.7890 train_loss=0.3131
|
| 170 |
+
step 5500 (epoch 2): val_spearman=0.7941 train_loss=0.3148
|
| 171 |
+
step 5600 (epoch 2): val_spearman=0.7873 train_loss=0.3165
|
| 172 |
+
step 5700 (epoch 2): val_spearman=0.8025 train_loss=0.3134
|
| 173 |
+
step 5800 (epoch 3): val_spearman=0.7950 train_loss=0.3151
|
| 174 |
+
step 5900 (epoch 3): val_spearman=0.8108 train_loss=0.3074
|
| 175 |
+
step 6000 (epoch 3): val_spearman=0.8236 train_loss=0.3037
|
| 176 |
+
step 6100 (epoch 3): val_spearman=0.8253 train_loss=0.3115
|
| 177 |
+
step 6200 (epoch 3): val_spearman=0.8008 train_loss=0.3036
|
| 178 |
+
step 6300 (epoch 3): val_spearman=0.8184 train_loss=0.3031
|
| 179 |
+
step 6400 (epoch 3): val_spearman=0.8036 train_loss=0.3127
|
| 180 |
+
step 6500 (epoch 3): val_spearman=0.8262 train_loss=0.3057
|
| 181 |
+
step 6600 (epoch 3): val_spearman=0.8286 train_loss=0.3057
|
| 182 |
+
step 6700 (epoch 3): val_spearman=0.8057 train_loss=0.3049
|
| 183 |
+
step 6800 (epoch 3): val_spearman=0.8081 train_loss=0.3065
|
| 184 |
+
step 6900 (epoch 3): val_spearman=0.8071 train_loss=0.3097
|
| 185 |
+
step 7000 (epoch 3): val_spearman=0.7703 train_loss=0.3047
|
| 186 |
+
step 7100 (epoch 3): val_spearman=0.7687 train_loss=0.3128
|
| 187 |
+
step 7200 (epoch 3): val_spearman=0.8192 train_loss=0.3081
|
| 188 |
+
step 7300 (epoch 3): val_spearman=0.7907 train_loss=0.3060
|
| 189 |
+
step 7400 (epoch 3): val_spearman=0.8335 train_loss=0.3078
|
| 190 |
+
step 7500 (epoch 3): val_spearman=0.8353 train_loss=0.3058
|
| 191 |
+
step 7600 (epoch 3): val_spearman=0.8262 train_loss=0.3030
|
| 192 |
+
step 7700 (epoch 3): val_spearman=0.7816 train_loss=0.3041
|
| 193 |
+
step 7800 (epoch 3): val_spearman=0.8260 train_loss=0.3092
|
| 194 |
+
step 7900 (epoch 3): val_spearman=0.8271 train_loss=0.3121
|
| 195 |
+
step 8000 (epoch 3): val_spearman=0.8045 train_loss=0.3060
|
| 196 |
+
step 8100 (epoch 3): val_spearman=0.8065 train_loss=0.3092
|
| 197 |
+
step 8200 (epoch 3): val_spearman=0.8127 train_loss=0.3056
|
| 198 |
+
step 8300 (epoch 3): val_spearman=0.8522 train_loss=0.3035
|
| 199 |
+
step 8400 (epoch 3): val_spearman=0.8279 train_loss=0.3032
|
| 200 |
+
step 8500 (epoch 3): val_spearman=0.7696 train_loss=0.3043
|
| 201 |
+
step 8600 (epoch 3): val_spearman=0.8019 train_loss=0.3091
|
| 202 |
+
step 8700 (epoch 4): val_spearman=0.8305 train_loss=0.3000
|
| 203 |
+
step 8800 (epoch 4): val_spearman=0.8327 train_loss=0.2937
|
| 204 |
+
step 8900 (epoch 4): val_spearman=0.8328 train_loss=0.2958
|
| 205 |
+
step 9000 (epoch 4): val_spearman=0.8410 train_loss=0.2934
|
| 206 |
+
step 9100 (epoch 4): val_spearman=0.8147 train_loss=0.2920
|
| 207 |
+
step 9200 (epoch 4): val_spearman=0.8393 train_loss=0.2939
|
| 208 |
+
step 9300 (epoch 4): val_spearman=0.8374 train_loss=0.2980
|
| 209 |
+
step 9400 (epoch 4): val_spearman=0.8148 train_loss=0.2965
|
| 210 |
+
step 9500 (epoch 4): val_spearman=0.8293 train_loss=0.2966
|
| 211 |
+
step 9600 (epoch 4): val_spearman=0.8338 train_loss=0.2936
|
| 212 |
+
step 9700 (epoch 4): val_spearman=0.8351 train_loss=0.2930
|
| 213 |
+
step 9800 (epoch 4): val_spearman=0.8428 train_loss=0.2960
|
| 214 |
+
step 9900 (epoch 4): val_spearman=0.8366 train_loss=0.2918
|
| 215 |
+
step 10000 (epoch 4): val_spearman=0.8328 train_loss=0.2919
|
| 216 |
+
step 10100 (epoch 4): val_spearman=0.7875 train_loss=0.2996
|
| 217 |
+
step 10200 (epoch 4): val_spearman=0.8348 train_loss=0.2947
|
| 218 |
+
step 10300 (epoch 4): val_spearman=0.8331 train_loss=0.2984
|
| 219 |
+
step 10400 (epoch 4): val_spearman=0.8280 train_loss=0.2997
|
| 220 |
+
step 10500 (epoch 4): val_spearman=0.8456 train_loss=0.2971
|
| 221 |
+
step 10600 (epoch 4): val_spearman=0.8506 train_loss=0.2946
|
| 222 |
+
step 10700 (epoch 4): val_spearman=0.8430 train_loss=0.2898
|
| 223 |
+
step 10800 (epoch 4): val_spearman=0.8138 train_loss=0.3017
|
| 224 |
+
step 10900 (epoch 4): val_spearman=0.8340 train_loss=0.2893
|
| 225 |
+
step 11000 (epoch 4): val_spearman=0.8224 train_loss=0.2953
|
| 226 |
+
step 11100 (epoch 4): val_spearman=0.8470 train_loss=0.2918
|
| 227 |
+
step 11200 (epoch 4): val_spearman=0.8494 train_loss=0.2945
|
| 228 |
+
step 11300 (epoch 4): val_spearman=0.8489 train_loss=0.2956
|
| 229 |
+
step 11400 (epoch 4): val_spearman=0.8205 train_loss=0.2984
|
| 230 |
+
step 11500 (epoch 4): val_spearman=0.8382 train_loss=0.2965
|
| 231 |
+
step 11600 (epoch 5): val_spearman=0.8409 train_loss=0.2880
|
| 232 |
+
step 11700 (epoch 5): val_spearman=0.8279 train_loss=0.2761
|
| 233 |
+
step 11800 (epoch 5): val_spearman=0.8502 train_loss=0.2739
|
| 234 |
+
step 11900 (epoch 5): val_spearman=0.8417 train_loss=0.2820
|
| 235 |
+
step 12000 (epoch 5): val_spearman=0.8297 train_loss=0.2757
|
| 236 |
+
step 12100 (epoch 5): val_spearman=0.8439 train_loss=0.2741
|
| 237 |
+
step 12200 (epoch 5): val_spearman=0.8294 train_loss=0.2787
|
| 238 |
+
step 12300 (epoch 5): val_spearman=0.8114 train_loss=0.2780
|
| 239 |
+
step 12400 (epoch 5): val_spearman=0.8258 train_loss=0.2758
|
| 240 |
+
step 12500 (epoch 5): val_spearman=0.8336 train_loss=0.2740
|
| 241 |
+
step 12600 (epoch 5): val_spearman=0.8418 train_loss=0.2790
|
| 242 |
+
step 12700 (epoch 5): val_spearman=0.8234 train_loss=0.2784
|
| 243 |
+
step 12800 (epoch 5): val_spearman=0.8309 train_loss=0.2772
|
| 244 |
+
step 12900 (epoch 5): val_spearman=0.8363 train_loss=0.2829
|
| 245 |
+
step 13000 (epoch 5): val_spearman=0.8387 train_loss=0.2722
|
| 246 |
+
step 13100 (epoch 5): val_spearman=0.8339 train_loss=0.2735
|
| 247 |
+
step 13200 (epoch 5): val_spearman=0.8509 train_loss=0.2766
|
| 248 |
+
step 13300 (epoch 5): val_spearman=0.8283 train_loss=0.2801
|
| 249 |
+
step 13400 (epoch 5): val_spearman=0.8264 train_loss=0.2779
|
| 250 |
+
step 13500 (epoch 5): val_spearman=0.8189 train_loss=0.2802
|
| 251 |
+
step 13600 (epoch 5): val_spearman=0.8364 train_loss=0.2863
|
| 252 |
+
step 13700 (epoch 5): val_spearman=0.8282 train_loss=0.2816
|
| 253 |
+
step 13800 (epoch 5): val_spearman=0.8332 train_loss=0.2771
|
| 254 |
+
step 13900 (epoch 5): val_spearman=0.8305 train_loss=0.2797
|
| 255 |
+
step 14000 (epoch 5): val_spearman=0.8279 train_loss=0.2781
|
| 256 |
+
step 14100 (epoch 5): val_spearman=0.8404 train_loss=0.2826
|
| 257 |
+
step 14200 (epoch 5): val_spearman=0.8544 train_loss=0.2747
|
| 258 |
+
step 14300 (epoch 5): val_spearman=0.8383 train_loss=0.2831
|
| 259 |
+
step 14400 (epoch 5): val_spearman=0.8369 train_loss=0.2850
|
| 260 |
+
step 14500 (epoch 6): val_spearman=0.8354 train_loss=0.2710
|
| 261 |
+
step 14600 (epoch 6): val_spearman=0.8300 train_loss=0.2508
|
| 262 |
+
step 14700 (epoch 6): val_spearman=0.8354 train_loss=0.2515
|
| 263 |
+
step 14800 (epoch 6): val_spearman=0.8400 train_loss=0.2499
|
| 264 |
+
step 14900 (epoch 6): val_spearman=0.8379 train_loss=0.2522
|
| 265 |
+
step 15000 (epoch 6): val_spearman=0.8232 train_loss=0.2493
|
| 266 |
+
step 15100 (epoch 6): val_spearman=0.8278 train_loss=0.2523
|
| 267 |
+
step 15200 (epoch 6): val_spearman=0.8269 train_loss=0.2551
|
| 268 |
+
step 15300 (epoch 6): val_spearman=0.8331 train_loss=0.2528
|
| 269 |
+
step 15400 (epoch 6): val_spearman=0.8324 train_loss=0.2549
|
| 270 |
+
step 15500 (epoch 6): val_spearman=0.8192 train_loss=0.2558
|
| 271 |
+
step 15600 (epoch 6): val_spearman=0.8158 train_loss=0.2544
|
| 272 |
+
step 15700 (epoch 6): val_spearman=0.8011 train_loss=0.2510
|
| 273 |
+
step 15800 (epoch 6): val_spearman=0.8387 train_loss=0.2553
|
| 274 |
+
step 15900 (epoch 6): val_spearman=0.8131 train_loss=0.2565
|
| 275 |
+
step 16000 (epoch 6): val_spearman=0.7877 train_loss=0.2558
|
| 276 |
+
step 16100 (epoch 6): val_spearman=0.7925 train_loss=0.2523
|
| 277 |
+
step 16200 (epoch 6): val_spearman=0.8176 train_loss=0.2547
|
| 278 |
+
step 16300 (epoch 6): val_spearman=0.8234 train_loss=0.2538
|
| 279 |
+
step 16400 (epoch 6): val_spearman=0.8266 train_loss=0.2546
|
| 280 |
+
step 16500 (epoch 6): val_spearman=0.7923 train_loss=0.2566
|
| 281 |
+
step 16600 (epoch 6): val_spearman=0.7765 train_loss=0.2552
|
| 282 |
+
step 16700 (epoch 6): val_spearman=0.8091 train_loss=0.2558
|
| 283 |
+
step 16800 (epoch 6): val_spearman=0.8167 train_loss=0.2600
|
| 284 |
+
step 16900 (epoch 6): val_spearman=0.8427 train_loss=0.2571
|
| 285 |
+
step 17000 (epoch 6): val_spearman=0.8231 train_loss=0.2560
|
| 286 |
+
step 17100 (epoch 6): val_spearman=0.8282 train_loss=0.2524
|
| 287 |
+
step 17200 (epoch 6): val_spearman=0.8178 train_loss=0.2491
|
| 288 |
+
step 17300 (epoch 6): val_spearman=0.8430 train_loss=0.2518
|
| 289 |
+
step 17400 (epoch 7): val_spearman=0.8298 train_loss=0.2417
|
| 290 |
+
step 17500 (epoch 7): val_spearman=0.8379 train_loss=0.2157
|
| 291 |
+
step 17600 (epoch 7): val_spearman=0.8314 train_loss=0.2148
|
| 292 |
+
step 17700 (epoch 7): val_spearman=0.8321 train_loss=0.2184
|
| 293 |
+
step 17800 (epoch 7): val_spearman=0.8276 train_loss=0.2160
|
| 294 |
+
step 17900 (epoch 7): val_spearman=0.8434 train_loss=0.2202
|
| 295 |
+
step 18000 (epoch 7): val_spearman=0.8198 train_loss=0.2173
|
| 296 |
+
step 18100 (epoch 7): val_spearman=0.8182 train_loss=0.2249
|
| 297 |
+
step 18200 (epoch 7): val_spearman=0.8574 train_loss=0.2230
|
| 298 |
+
step 18300 (epoch 7): val_spearman=0.7976 train_loss=0.2188
|
| 299 |
+
step 18400 (epoch 7): val_spearman=0.8164 train_loss=0.2223
|
| 300 |
+
step 18500 (epoch 7): val_spearman=0.8203 train_loss=0.2225
|
| 301 |
+
step 18600 (epoch 7): val_spearman=0.8036 train_loss=0.2179
|
| 302 |
+
step 18700 (epoch 7): val_spearman=0.8321 train_loss=0.2166
|
| 303 |
+
step 18800 (epoch 7): val_spearman=0.8247 train_loss=0.2284
|
| 304 |
+
step 18900 (epoch 7): val_spearman=0.8291 train_loss=0.2275
|
| 305 |
+
step 19000 (epoch 7): val_spearman=0.8247 train_loss=0.2256
|
| 306 |
+
step 19100 (epoch 7): val_spearman=0.8103 train_loss=0.2252
|
| 307 |
+
step 19200 (epoch 7): val_spearman=0.8200 train_loss=0.2215
|
| 308 |
+
step 19300 (epoch 7): val_spearman=0.7826 train_loss=0.2254
|
| 309 |
+
step 19400 (epoch 7): val_spearman=0.8030 train_loss=0.2262
|
| 310 |
+
step 19500 (epoch 7): val_spearman=0.7987 train_loss=0.2239
|
| 311 |
+
step 19600 (epoch 7): val_spearman=0.8278 train_loss=0.2294
|
| 312 |
+
step 19700 (epoch 7): val_spearman=0.8073 train_loss=0.2216
|
| 313 |
+
step 19800 (epoch 7): val_spearman=0.8380 train_loss=0.2222
|
| 314 |
+
step 19900 (epoch 7): val_spearman=0.8328 train_loss=0.2188
|
| 315 |
+
step 20000 (epoch 7): val_spearman=0.8235 train_loss=0.2234
|
| 316 |
+
step 20100 (epoch 7): val_spearman=0.8227 train_loss=0.2302
|
| 317 |
+
step 20200 (epoch 7): val_spearman=0.8375 train_loss=0.2271
|
| 318 |
+
step 20300 (epoch 8): val_spearman=0.8444 train_loss=0.2103
|
| 319 |
+
step 20400 (epoch 8): val_spearman=0.8245 train_loss=0.1798
|
| 320 |
+
step 20500 (epoch 8): val_spearman=0.8064 train_loss=0.1790
|
| 321 |
+
step 20600 (epoch 8): val_spearman=0.8196 train_loss=0.1853
|
| 322 |
+
step 20700 (epoch 8): val_spearman=0.8127 train_loss=0.1830
|
| 323 |
+
step 20800 (epoch 8): val_spearman=0.8184 train_loss=0.1805
|
| 324 |
+
step 20900 (epoch 8): val_spearman=0.8061 train_loss=0.1858
|
| 325 |
+
step 21000 (epoch 8): val_spearman=0.8104 train_loss=0.1858
|
| 326 |
+
step 21100 (epoch 8): val_spearman=0.8109 train_loss=0.1849
|
| 327 |
+
step 21200 (epoch 8): val_spearman=0.8162 train_loss=0.1916
|
| 328 |
+
step 21300 (epoch 8): val_spearman=0.8056 train_loss=0.1876
|
| 329 |
+
step 21400 (epoch 8): val_spearman=0.8211 train_loss=0.1870
|
| 330 |
+
step 21500 (epoch 8): val_spearman=0.8292 train_loss=0.1864
|
| 331 |
+
step 21600 (epoch 8): val_spearman=0.8322 train_loss=0.1862
|
| 332 |
+
step 21700 (epoch 8): val_spearman=0.8245 train_loss=0.1868
|
| 333 |
+
step 21800 (epoch 8): val_spearman=0.8224 train_loss=0.1895
|
| 334 |
+
step 21900 (epoch 8): val_spearman=0.8371 train_loss=0.1901
|
| 335 |
+
step 22000 (epoch 8): val_spearman=0.8341 train_loss=0.1872
|
| 336 |
+
step 22100 (epoch 8): val_spearman=0.8309 train_loss=0.1879
|
| 337 |
+
step 22200 (epoch 8): val_spearman=0.8356 train_loss=0.1898
|
| 338 |
+
step 22300 (epoch 8): val_spearman=0.8307 train_loss=0.1876
|
| 339 |
+
step 22400 (epoch 8): val_spearman=0.8190 train_loss=0.1863
|
| 340 |
+
step 22500 (epoch 8): val_spearman=0.8232 train_loss=0.1885
|
| 341 |
+
step 22600 (epoch 8): val_spearman=0.8472 train_loss=0.1899
|
| 342 |
+
step 22700 (epoch 8): val_spearman=0.8271 train_loss=0.1910
|
| 343 |
+
step 22800 (epoch 8): val_spearman=0.8417 train_loss=0.1898
|
| 344 |
+
step 22900 (epoch 8): val_spearman=0.8468 train_loss=0.1891
|
| 345 |
+
step 23000 (epoch 8): val_spearman=0.8162 train_loss=0.1929
|
| 346 |
+
step 23100 (epoch 8): val_spearman=0.8312 train_loss=0.1861
|
| 347 |
+
step 23200 (epoch 9): val_spearman=0.8483 train_loss=0.1706
|
| 348 |
+
step 23300 (epoch 9): val_spearman=0.8381 train_loss=0.1465
|
| 349 |
+
step 23400 (epoch 9): val_spearman=0.8448 train_loss=0.1463
|
| 350 |
+
step 23500 (epoch 9): val_spearman=0.8297 train_loss=0.1476
|
| 351 |
+
step 23600 (epoch 9): val_spearman=0.8427 train_loss=0.1479
|
| 352 |
+
step 23700 (epoch 9): val_spearman=0.8299 train_loss=0.1492
|
| 353 |
+
step 23800 (epoch 9): val_spearman=0.8290 train_loss=0.1512
|
| 354 |
+
step 23900 (epoch 9): val_spearman=0.8368 train_loss=0.1505
|
| 355 |
+
step 24000 (epoch 9): val_spearman=0.8186 train_loss=0.1532
|
| 356 |
+
step 24100 (epoch 9): val_spearman=0.8286 train_loss=0.1496
|
| 357 |
+
step 24200 (epoch 9): val_spearman=0.8415 train_loss=0.1507
|
| 358 |
+
step 24300 (epoch 9): val_spearman=0.8488 train_loss=0.1513
|
| 359 |
+
step 24400 (epoch 9): val_spearman=0.8498 train_loss=0.1497
|
| 360 |
+
step 24500 (epoch 9): val_spearman=0.8522 train_loss=0.1560
|
| 361 |
+
step 24600 (epoch 9): val_spearman=0.8513 train_loss=0.1490
|
| 362 |
+
step 24700 (epoch 9): val_spearman=0.8284 train_loss=0.1543
|
| 363 |
+
step 24800 (epoch 9): val_spearman=0.8234 train_loss=0.1542
|
| 364 |
+
step 24900 (epoch 9): val_spearman=0.8147 train_loss=0.1525
|
| 365 |
+
step 25000 (epoch 9): val_spearman=0.8215 train_loss=0.1543
|
| 366 |
+
step 25100 (epoch 9): val_spearman=0.8334 train_loss=0.1550
|
| 367 |
+
step 25200 (epoch 9): val_spearman=0.8295 train_loss=0.1565
|
| 368 |
+
step 25300 (epoch 9): val_spearman=0.8220 train_loss=0.1602
|
| 369 |
+
step 25400 (epoch 9): val_spearman=0.8320 train_loss=0.1590
|
| 370 |
+
step 25500 (epoch 9): val_spearman=0.8422 train_loss=0.1617
|
| 371 |
+
step 25600 (epoch 9): val_spearman=0.8221 train_loss=0.1546
|
| 372 |
+
step 25700 (epoch 9): val_spearman=0.8255 train_loss=0.1555
|
| 373 |
+
step 25800 (epoch 9): val_spearman=0.8234 train_loss=0.1589
|
| 374 |
+
step 25900 (epoch 9): val_spearman=0.8169 train_loss=0.1547
|
| 375 |
+
step 26000 (epoch 9): val_spearman=0.8078 train_loss=0.1585
|
| 376 |
+
step 26100 (epoch 10): val_spearman=0.8251 train_loss=0.1381
|
| 377 |
+
step 26200 (epoch 10): val_spearman=0.8006 train_loss=0.1157
|
| 378 |
+
step 26300 (epoch 10): val_spearman=0.8446 train_loss=0.1167
|
| 379 |
+
step 26400 (epoch 10): val_spearman=0.8497 train_loss=0.1171
|
| 380 |
+
step 26500 (epoch 10): val_spearman=0.8121 train_loss=0.1210
|
| 381 |
+
step 26600 (epoch 10): val_spearman=0.8385 train_loss=0.1152
|
| 382 |
+
step 26700 (epoch 10): val_spearman=0.8209 train_loss=0.1181
|
| 383 |
+
step 26800 (epoch 10): val_spearman=0.8127 train_loss=0.1227
|
| 384 |
+
step 26900 (epoch 10): val_spearman=0.7972 train_loss=0.1243
|
| 385 |
+
step 27000 (epoch 10): val_spearman=0.8212 train_loss=0.1225
|
| 386 |
+
step 27100 (epoch 10): val_spearman=0.8100 train_loss=0.1228
|
| 387 |
+
step 27200 (epoch 10): val_spearman=0.8089 train_loss=0.1275
|
| 388 |
+
step 27300 (epoch 10): val_spearman=0.8190 train_loss=0.1242
|
| 389 |
+
step 27400 (epoch 10): val_spearman=0.8336 train_loss=0.1245
|
| 390 |
+
step 27500 (epoch 10): val_spearman=0.8118 train_loss=0.1229
|
| 391 |
+
step 27600 (epoch 10): val_spearman=0.8238 train_loss=0.1256
|
| 392 |
+
step 27700 (epoch 10): val_spearman=0.8090 train_loss=0.1257
|
| 393 |
+
step 27800 (epoch 10): val_spearman=0.7854 train_loss=0.1272
|
| 394 |
+
step 27900 (epoch 10): val_spearman=0.8196 train_loss=0.1283
|
| 395 |
+
step 28000 (epoch 10): val_spearman=0.8283 train_loss=0.1280
|
| 396 |
+
step 28100 (epoch 10): val_spearman=0.8144 train_loss=0.1276
|
| 397 |
+
step 28200 (epoch 10): val_spearman=0.8124 train_loss=0.1256
|
| 398 |
+
step 28300 (epoch 10): val_spearman=0.8188 train_loss=0.1299
|
| 399 |
+
step 28400 (epoch 10): val_spearman=0.7993 train_loss=0.1271
|
| 400 |
+
step 28500 (epoch 10): val_spearman=0.8174 train_loss=0.1266
|
| 401 |
+
step 28600 (epoch 10): val_spearman=0.7845 train_loss=0.1284
|
| 402 |
+
step 28700 (epoch 10): val_spearman=0.8076 train_loss=0.1269
|
| 403 |
+
step 28800 (epoch 10): val_spearman=0.8182 train_loss=0.1328
|
| 404 |
+
step 28900 (epoch 10): val_spearman=0.8231 train_loss=0.1283
|
| 405 |
+
step 28930 (epoch 11): val_spearman=0.8038 train_loss=0.1253
|
| 406 |
+
|
| 407 |
+
============================================================
|
outputs/pep-affibody-ablation-fe/libB_pseudo_bf16/train.log
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|