| NUM_GPUS=1 | |
| MASTER_ADDR=ip-10-0-133-32 | |
| MASTER_PORT=13726 | |
| WORLD_SIZE=1 | |
| ------ ARGS ------- | |
| Namespace(found_model_name='HCPflat_large_gsrFalse_', epoch_checkpoint='epoch99.pth', model_suffix='beta', hcp_flat_path='/weka/proj-medarc/shared/HCP-Flat', batch_size=16, wandb_log=True, num_epochs=20, lr_scheduler_type='cycle', save_ckpt=False, seed=42, max_lr=0.0003, target='sex', num_workers=15, weight_decay=0.001, global_pool=True) | |
| outdir /weka/proj-fmri/ckadirt/fMRI-foundation-model/src/checkpoints/HCPflat_large_gsrFalse_ | |
| Loaded config.yaml from ckpt folder /weka/proj-fmri/ckadirt/fMRI-foundation-model/src/checkpoints/HCPflat_large_gsrFalse_ | |
| __CONFIG__ | |
| base_lr = 0.001 | |
| batch_size = 32 | |
| ckpt_interval = 5 | |
| ckpt_saving = True | |
| cls_embed = True | |
| contrastive_loss_weight = 1.0 | |
| datasets_to_include = HCP | |
| decoder_embed_dim = 512 | |
| grad_accumulation_steps = 1 | |
| grad_clip = 1.0 | |
| gsr = False | |
| hcp_flat_path = /weka/proj-medarc/shared/HCP-Flat | |
| mask_ratio = 0.75 | |
| model_name = HCPflat_large_gsrFalse_ | |
| no_qkv_bias = False | |
| norm_pix_loss = False | |
| nsd_flat_path = /weka/proj-medarc/shared/NSD-Flat | |
| num_epochs = 100 | |
| num_frames = 16 | |
| num_samples_per_epoch = 200000 | |
| num_workers = 10 | |
| patch_size = 16 | |
| pct_masks_to_decode = 1 | |
| plotting = True | |
| pred_t_dim = 8 | |
| print_interval = 20 | |
| probe_base_lr = 0.0003 | |
| probe_batch_size = 8 | |
| probe_num_epochs = 30 | |
| probe_num_samples_per_epoch = 100000 | |
| resume_from_ckpt = True | |
| seed = 42 | |
| sep_pos_embed = True | |
| t_patch_size = 2 | |
| test_num_samples_per_epoch = 50000 | |
| test_set = False | |
| trunc_init = False | |
| use_contrastive_loss = False | |
| wandb_log = True | |
| WORLD_SIZE=1 | |
| PID of this process = 1894104 | |
| global_pool = True | |
| gsr = False | |
| Creating datasets | |
| Datasets ready | |
| img_size (144, 320) patch_size (16, 16) frames 16 t_patch_size 2 | |
| model initialized | |
| latest_checkpoint: epoch99.pth | |
| Loaded checkpoint epoch99.pth from /weka/proj-fmri/ckadirt/fMRI-foundation-model/src/checkpoints/HCPflat_large_gsrFalse_ | |
| Input dimension: 1024 | |
| total_steps 139140 | |
| wandb_config: | |
| {'model_name': 'HCPflat_large_gsrFalse__HCP_FT_sex', 'batch_size': 16, 'weight_decay': 0.001, 'num_epochs': 20, 'seed': 42, 'lr_scheduler_type': 'cycle', 'save_ckpt': False, 'max_lr': 0.0003, 'target': 'sex', 'num_workers': 15} | |
| wandb_id: HCPflat_large_gsrFalse__beta_sex_HCPFT_83810 | |
| Step [100/6957] - Training Loss: 0.3922 - Training Accuracy: 77.19% | |
| Step [200/6957] - Training Loss: 0.3031 - Training Accuracy: 80.75% | |
| Step [300/6957] - Training Loss: 0.3164 - Training Accuracy: 82.96% | |
| Step [400/6957] - Training Loss: 0.4025 - Training Accuracy: 83.42% | |
| Step [500/6957] - Training Loss: 0.1198 - Training Accuracy: 84.53% | |
| Step [600/6957] - Training Loss: 0.3188 - Training Accuracy: 85.08% | |
| Step [700/6957] - Training Loss: 0.5495 - Training Accuracy: 85.61% | |
| Step [800/6957] - Training Loss: 0.3379 - Training Accuracy: 86.04% | |
| Step [900/6957] - Training Loss: 0.1062 - Training Accuracy: 86.17% | |
| Step [1000/6957] - Training Loss: 0.4039 - Training Accuracy: 86.65% | |
| Step [1100/6957] - Training Loss: 0.0854 - Training Accuracy: 87.06% | |
| Step [1200/6957] - Training Loss: 0.1939 - Training Accuracy: 87.29% | |
| Step [1300/6957] - Training Loss: 0.1283 - Training Accuracy: 87.54% | |
| Step [1400/6957] - Training Loss: 0.1615 - Training Accuracy: 87.72% | |
| Step [1500/6957] - Training Loss: 0.4869 - Training Accuracy: 87.78% | |
| Step [1600/6957] - Training Loss: 0.4883 - Training Accuracy: 87.90% | |
| Step [1700/6957] - Training Loss: 0.2812 - Training Accuracy: 88.06% | |
| Step [1800/6957] - Training Loss: 0.0326 - Training Accuracy: 88.27% | |
| Step [1900/6957] - Training Loss: 0.4183 - Training Accuracy: 88.42% | |
| Step [2000/6957] - Training Loss: 0.0631 - Training Accuracy: 88.63% | |
| Step [2100/6957] - Training Loss: 0.0572 - Training Accuracy: 88.73% | |
| Step [2200/6957] - Training Loss: 0.1543 - Training Accuracy: 88.78% | |
| Step [2300/6957] - Training Loss: 0.3029 - Training Accuracy: 88.75% | |
| Step [2400/6957] - Training Loss: 0.2348 - Training Accuracy: 88.88% | |
| Step [2500/6957] - Training Loss: 0.7931 - Training Accuracy: 89.00% | |
| Step [2600/6957] - Training Loss: 0.0864 - Training Accuracy: 89.02% | |
| Step [2700/6957] - Training Loss: 0.0116 - Training Accuracy: 89.06% | |
| Step [2800/6957] - Training Loss: 0.0768 - Training Accuracy: 89.08% | |
| Step [2900/6957] - Training Loss: 0.1840 - Training Accuracy: 89.12% | |
| Step [3000/6957] - Training Loss: 0.1375 - Training Accuracy: 89.21% | |
| Step [3100/6957] - Training Loss: 0.3402 - Training Accuracy: 89.26% | |
| Step [3200/6957] - Training Loss: 0.2121 - Training Accuracy: 89.30% | |
| Step [3300/6957] - Training Loss: 0.1422 - Training Accuracy: 89.30% | |
| Step [3400/6957] - Training Loss: 0.1266 - Training Accuracy: 89.38% | |
| Step [3500/6957] - Training Loss: 0.1457 - Training Accuracy: 89.41% | |
| Step [3600/6957] - Training Loss: 0.2656 - Training Accuracy: 89.47% | |
| Step [3700/6957] - Training Loss: 0.3446 - Training Accuracy: 89.50% | |
| Step [3800/6957] - Training Loss: 0.1169 - Training Accuracy: 89.55% | |
| Step [3900/6957] - Training Loss: 0.0928 - Training Accuracy: 89.53% | |
| Step [4000/6957] - Training Loss: 0.1900 - Training Accuracy: 89.58% | |
| Step [4100/6957] - Training Loss: 0.1335 - Training Accuracy: 89.61% | |
| Step [4200/6957] - Training Loss: 0.1863 - Training Accuracy: 89.57% | |
| Step [4300/6957] - Training Loss: 0.3499 - Training Accuracy: 89.64% | |
| Step [4400/6957] - Training Loss: 0.2883 - Training Accuracy: 89.65% | |
| Step [4500/6957] - Training Loss: 0.1651 - Training Accuracy: 89.71% | |
| Step [4600/6957] - Training Loss: 0.2184 - Training Accuracy: 89.69% | |
| Step [4700/6957] - Training Loss: 0.1749 - Training Accuracy: 89.65% | |
| Step [4800/6957] - Training Loss: 0.1940 - Training Accuracy: 89.71% | |
| Step [4900/6957] - Training Loss: 0.2742 - Training Accuracy: 89.71% | |
| Step [5000/6957] - Training Loss: 0.0571 - Training Accuracy: 89.68% | |
| Step [5100/6957] - Training Loss: 0.5313 - Training Accuracy: 89.70% | |
| Step [5200/6957] - Training Loss: 0.6183 - Training Accuracy: 89.71% | |
| Step [5300/6957] - Training Loss: 0.1989 - Training Accuracy: 89.71% | |
| Step [5400/6957] - Training Loss: 0.2805 - Training Accuracy: 89.70% | |
| Step [5500/6957] - Training Loss: 0.2530 - Training Accuracy: 89.69% | |
| Step [5600/6957] - Training Loss: 0.1504 - Training Accuracy: 89.73% | |
| Step [5700/6957] - Training Loss: 0.0307 - Training Accuracy: 89.79% | |
| Step [5800/6957] - Training Loss: 0.0681 - Training Accuracy: 89.74% | |
| Step [5900/6957] - Training Loss: 0.0534 - Training Accuracy: 89.75% | |
| Step [6000/6957] - Training Loss: 0.1133 - Training Accuracy: 89.73% | |
| Step [6100/6957] - Training Loss: 0.2328 - Training Accuracy: 89.72% | |
| Step [6200/6957] - Training Loss: 0.4813 - Training Accuracy: 89.75% | |
| Step [6300/6957] - Training Loss: 0.1921 - Training Accuracy: 89.74% | |
| Step [6400/6957] - Training Loss: 0.6623 - Training Accuracy: 89.76% | |
| Step [6500/6957] - Training Loss: 0.1625 - Training Accuracy: 89.78% | |
| Step [6600/6957] - Training Loss: 0.1878 - Training Accuracy: 89.77% | |
| Step [6700/6957] - Training Loss: 0.0457 - Training Accuracy: 89.76% | |
| Step [6800/6957] - Training Loss: 0.1311 - Training Accuracy: 89.77% | |
| Step [6900/6957] - Training Loss: 0.7622 - Training Accuracy: 89.78% | |
| Epoch [1/20] - Training Loss: 0.2437, Training Accuracy: 89.75% - Validation Loss: 0.4896, Validation Accuracy: 80.52% | |
| Step [100/6957] - Training Loss: 0.2772 - Training Accuracy: 91.56% | |
| Step [200/6957] - Training Loss: 0.2397 - Training Accuracy: 91.66% | |
| Step [300/6957] - Training Loss: 0.1749 - Training Accuracy: 91.15% | |
| Step [400/6957] - Training Loss: 0.1130 - Training Accuracy: 90.69% | |
| Step [500/6957] - Training Loss: 0.1125 - Training Accuracy: 90.53% | |
| Step [600/6957] - Training Loss: 0.4399 - Training Accuracy: 90.41% | |
| Step [700/6957] - Training Loss: 0.1879 - Training Accuracy: 90.27% | |
| Step [800/6957] - Training Loss: 0.2644 - Training Accuracy: 90.15% | |
| Step [900/6957] - Training Loss: 0.4248 - Training Accuracy: 89.99% | |
| Step [1000/6957] - Training Loss: 0.1605 - Training Accuracy: 89.98% | |
| Step [1100/6957] - Training Loss: 0.4203 - Training Accuracy: 89.92% | |
| Step [1200/6957] - Training Loss: 0.2863 - Training Accuracy: 89.96% | |
| Step [1300/6957] - Training Loss: 0.2773 - Training Accuracy: 89.73% | |
| Step [1400/6957] - Training Loss: 0.4140 - Training Accuracy: 89.62% | |
| Step [1500/6957] - Training Loss: 0.1883 - Training Accuracy: 89.63% | |
| Step [1600/6957] - Training Loss: 0.1607 - Training Accuracy: 89.59% | |
| Step [1700/6957] - Training Loss: 1.0266 - Training Accuracy: 89.40% | |
| Step [1800/6957] - Training Loss: 0.2373 - Training Accuracy: 89.26% | |
| Step [1900/6957] - Training Loss: 0.2210 - Training Accuracy: 89.27% | |
| Step [2000/6957] - Training Loss: 0.1980 - Training Accuracy: 89.18% | |
| Step [2100/6957] - Training Loss: 0.0986 - Training Accuracy: 89.12% | |
| Step [2200/6957] - Training Loss: 0.2032 - Training Accuracy: 89.14% | |
| Step [2300/6957] - Training Loss: 0.2904 - Training Accuracy: 89.07% | |
| Step [2400/6957] - Training Loss: 0.4172 - Training Accuracy: 89.06% | |
| Step [2500/6957] - Training Loss: 0.1630 - Training Accuracy: 89.00% | |
| Step [2600/6957] - Training Loss: 0.1731 - Training Accuracy: 89.01% | |
| Step [2700/6957] - Training Loss: 0.0868 - Training Accuracy: 88.96% | |
| Step [2800/6957] - Training Loss: 0.4874 - Training Accuracy: 88.95% | |
| Step [2900/6957] - Training Loss: 0.2219 - Training Accuracy: 88.96% | |
| Step [3000/6957] - Training Loss: 0.6419 - Training Accuracy: 88.92% | |
| Step [3100/6957] - Training Loss: 0.1915 - Training Accuracy: 88.81% | |
| Step [3200/6957] - Training Loss: 0.2766 - Training Accuracy: 88.77% | |
| Step [3300/6957] - Training Loss: 0.6664 - Training Accuracy: 88.69% | |
| Step [3400/6957] - Training Loss: 0.2272 - Training Accuracy: 88.63% | |
| Step [3500/6957] - Training Loss: 0.5269 - Training Accuracy: 88.60% | |
| Step [3600/6957] - Training Loss: 0.8040 - Training Accuracy: 88.55% | |
| Step [3700/6957] - Training Loss: 0.2381 - Training Accuracy: 88.48% | |
| Step [3800/6957] - Training Loss: 0.3181 - Training Accuracy: 88.38% | |
| Step [3900/6957] - Training Loss: 0.3124 - Training Accuracy: 88.35% | |
| Step [4000/6957] - Training Loss: 0.2964 - Training Accuracy: 88.32% | |
| Step [4100/6957] - Training Loss: 0.3694 - Training Accuracy: 88.25% | |
| Step [4200/6957] - Training Loss: 0.5149 - Training Accuracy: 88.20% | |
| Step [4300/6957] - Training Loss: 0.2386 - Training Accuracy: 88.14% | |
| Step [4400/6957] - Training Loss: 0.1465 - Training Accuracy: 88.08% | |
| Step [4500/6957] - Training Loss: 0.0805 - Training Accuracy: 88.04% | |
| Step [4600/6957] - Training Loss: 0.2600 - Training Accuracy: 87.98% | |
| Step [4700/6957] - Training Loss: 0.5791 - Training Accuracy: 87.96% | |
| Step [4800/6957] - Training Loss: 0.5183 - Training Accuracy: 87.89% | |
| Step [4900/6957] - Training Loss: 0.1225 - Training Accuracy: 87.83% | |
| Step [5000/6957] - Training Loss: 0.3032 - Training Accuracy: 87.79% | |
| Step [5100/6957] - Training Loss: 0.3162 - Training Accuracy: 87.74% | |
| Step [5200/6957] - Training Loss: 0.3099 - Training Accuracy: 87.68% | |
| Step [5300/6957] - Training Loss: 0.6100 - Training Accuracy: 87.63% | |
| Step [5400/6957] - Training Loss: 0.4826 - Training Accuracy: 87.63% | |
| Step [5500/6957] - Training Loss: 0.4072 - Training Accuracy: 87.60% | |
| Step [5600/6957] - Training Loss: 0.2029 - Training Accuracy: 87.56% | |
| Step [5700/6957] - Training Loss: 0.4778 - Training Accuracy: 87.50% | |
| Step [5800/6957] - Training Loss: 0.4601 - Training Accuracy: 87.47% | |
| Step [5900/6957] - Training Loss: 0.7077 - Training Accuracy: 87.44% | |
| Step [6000/6957] - Training Loss: 0.2198 - Training Accuracy: 87.40% | |
| Step [6100/6957] - Training Loss: 0.1838 - Training Accuracy: 87.38% | |
| Step [6200/6957] - Training Loss: 0.1775 - Training Accuracy: 87.34% | |
| Step [6300/6957] - Training Loss: 0.4879 - Training Accuracy: 87.32% | |
| Step [6400/6957] - Training Loss: 0.5445 - Training Accuracy: 87.29% | |
| Step [6500/6957] - Training Loss: 0.3480 - Training Accuracy: 87.26% | |
| Step [6600/6957] - Training Loss: 0.3990 - Training Accuracy: 87.25% | |
| Step [6700/6957] - Training Loss: 0.2598 - Training Accuracy: 87.24% | |
| Step [6800/6957] - Training Loss: 0.1453 - Training Accuracy: 87.21% | |
| Step [6900/6957] - Training Loss: 0.5141 - Training Accuracy: 87.18% | |
| Epoch [2/20] - Training Loss: 0.2976, Training Accuracy: 87.19% - Validation Loss: 0.6730, Validation Accuracy: 78.65% | |
| Step [100/6957] - Training Loss: 0.4532 - Training Accuracy: 88.25% | |
| Step [200/6957] - Training Loss: 0.0884 - Training Accuracy: 89.25% | |
| Step [300/6957] - Training Loss: 0.0801 - Training Accuracy: 88.65% | |
| Step [400/6957] - Training Loss: 0.1893 - Training Accuracy: 88.20% | |
| Step [500/6957] - Training Loss: 0.7368 - Training Accuracy: 88.34% | |
| Step [600/6957] - Training Loss: 0.0517 - Training Accuracy: 88.60% | |
| Step [700/6957] - Training Loss: 0.2540 - Training Accuracy: 88.60% | |
| Step [800/6957] - Training Loss: 0.2784 - Training Accuracy: 88.52% | |
| Step [900/6957] - Training Loss: 0.1315 - Training Accuracy: 88.52% | |
| Step [1000/6957] - Training Loss: 0.4281 - Training Accuracy: 88.51% | |
| Step [1100/6957] - Training Loss: 0.3333 - Training Accuracy: 88.36% | |
| Step [1200/6957] - Training Loss: 0.3302 - Training Accuracy: 88.44% | |
| Step [1300/6957] - Training Loss: 0.3849 - Training Accuracy: 88.52% | |
| Step [1400/6957] - Training Loss: 0.0579 - Training Accuracy: 88.42% | |
| Step [1500/6957] - Training Loss: 0.4995 - Training Accuracy: 88.40% | |
| Step [1600/6957] - Training Loss: 0.3993 - Training Accuracy: 88.26% | |
| Step [1700/6957] - Training Loss: 0.3876 - Training Accuracy: 88.37% | |
| Step [1800/6957] - Training Loss: 0.2100 - Training Accuracy: 88.40% | |
| Step [1900/6957] - Training Loss: 0.2273 - Training Accuracy: 88.35% | |
| Step [2000/6957] - Training Loss: 0.0775 - Training Accuracy: 88.37% | |
| Step [2100/6957] - Training Loss: 0.1250 - Training Accuracy: 88.49% | |
| Step [2200/6957] - Training Loss: 0.2354 - Training Accuracy: 88.48% | |
| Step [2300/6957] - Training Loss: 0.3245 - Training Accuracy: 88.38% | |
| Step [2400/6957] - Training Loss: 0.1378 - Training Accuracy: 88.48% | |
| Step [2500/6957] - Training Loss: 0.3975 - Training Accuracy: 88.66% | |
| Step [2600/6957] - Training Loss: 0.1956 - Training Accuracy: 88.67% | |
| Step [2700/6957] - Training Loss: 0.0942 - Training Accuracy: 88.66% | |
| Step [2800/6957] - Training Loss: 0.0492 - Training Accuracy: 88.70% | |
| Step [2900/6957] - Training Loss: 0.3040 - Training Accuracy: 88.73% | |
| Step [3000/6957] - Training Loss: 0.3643 - Training Accuracy: 88.77% | |
| Step [3100/6957] - Training Loss: 0.0943 - Training Accuracy: 88.83% | |
| Step [3200/6957] - Training Loss: 0.0873 - Training Accuracy: 88.88% | |
| Step [3300/6957] - Training Loss: 0.1579 - Training Accuracy: 88.92% | |
| Step [3400/6957] - Training Loss: 0.1507 - Training Accuracy: 88.98% | |
| Step [3500/6957] - Training Loss: 0.3810 - Training Accuracy: 89.04% | |
| Step [3600/6957] - Training Loss: 0.2306 - Training Accuracy: 89.01% | |
| Step [3700/6957] - Training Loss: 0.1091 - Training Accuracy: 89.03% | |
| Step [3800/6957] - Training Loss: 0.2266 - Training Accuracy: 89.07% | |
| Step [3900/6957] - Training Loss: 0.2083 - Training Accuracy: 89.12% | |
| Step [4000/6957] - Training Loss: 0.3154 - Training Accuracy: 89.13% | |
| Step [4100/6957] - Training Loss: 0.3363 - Training Accuracy: 89.16% | |
| Step [4200/6957] - Training Loss: 0.0907 - Training Accuracy: 89.22% | |
| Step [4300/6957] - Training Loss: 0.1546 - Training Accuracy: 89.24% | |
| Step [4400/6957] - Training Loss: 0.0978 - Training Accuracy: 89.28% | |
| Step [4500/6957] - Training Loss: 0.5293 - Training Accuracy: 89.32% | |
| Step [4600/6957] - Training Loss: 0.1854 - Training Accuracy: 89.35% | |
| Step [4700/6957] - Training Loss: 0.0088 - Training Accuracy: 89.41% | |
| Step [4800/6957] - Training Loss: 0.2089 - Training Accuracy: 89.44% | |
| Step [4900/6957] - Training Loss: 0.1408 - Training Accuracy: 89.47% | |
| Step [5000/6957] - Training Loss: 0.2790 - Training Accuracy: 89.51% | |
| Step [5100/6957] - Training Loss: 0.2580 - Training Accuracy: 89.52% | |
| Step [5200/6957] - Training Loss: 0.0881 - Training Accuracy: 89.56% | |
| Step [5300/6957] - Training Loss: 0.0627 - Training Accuracy: 89.62% | |
| Step [5400/6957] - Training Loss: 0.1289 - Training Accuracy: 89.65% | |
| Step [5500/6957] - Training Loss: 0.0932 - Training Accuracy: 89.69% | |
| Step [5600/6957] - Training Loss: 0.2704 - Training Accuracy: 89.70% | |
| Step [5700/6957] - Training Loss: 0.3665 - Training Accuracy: 89.73% | |
| Step [5800/6957] - Training Loss: 0.1076 - Training Accuracy: 89.76% | |
| Step [5900/6957] - Training Loss: 0.1009 - Training Accuracy: 89.80% | |
| Step [6000/6957] - Training Loss: 0.0623 - Training Accuracy: 89.83% | |
| Step [6100/6957] - Training Loss: 0.2482 - Training Accuracy: 89.87% | |
| Step [6200/6957] - Training Loss: 0.0376 - Training Accuracy: 89.92% | |
| Step [6300/6957] - Training Loss: 0.1291 - Training Accuracy: 89.93% | |
| Step [6400/6957] - Training Loss: 0.1528 - Training Accuracy: 89.99% | |
| Step [6500/6957] - Training Loss: 0.1459 - Training Accuracy: 90.03% | |
| Step [6600/6957] - Training Loss: 0.2658 - Training Accuracy: 90.05% | |
| Step [6700/6957] - Training Loss: 0.1367 - Training Accuracy: 90.12% | |
| Step [6800/6957] - Training Loss: 0.4000 - Training Accuracy: 90.13% | |
| Step [6900/6957] - Training Loss: 0.1692 - Training Accuracy: 90.17% | |
| Epoch [3/20] - Training Loss: 0.2368, Training Accuracy: 90.18% - Validation Loss: 0.6234, Validation Accuracy: 76.45% | |
| Step [100/6957] - Training Loss: 0.0649 - Training Accuracy: 94.06% | |
| Step [200/6957] - Training Loss: 0.0303 - Training Accuracy: 93.94% | |
| Step [300/6957] - Training Loss: 0.0096 - Training Accuracy: 94.02% | |
| Step [400/6957] - Training Loss: 0.2064 - Training Accuracy: 94.05% | |
| Step [500/6957] - Training Loss: 0.0261 - Training Accuracy: 94.05% | |
| Step [600/6957] - Training Loss: 0.0420 - Training Accuracy: 94.04% | |
| Step [700/6957] - Training Loss: 0.1935 - Training Accuracy: 93.89% | |
| Step [800/6957] - Training Loss: 0.7093 - Training Accuracy: 93.89% | |
| Step [900/6957] - Training Loss: 0.5725 - Training Accuracy: 93.81% | |
| Step [1000/6957] - Training Loss: 0.0427 - Training Accuracy: 93.67% | |
| Step [1100/6957] - Training Loss: 0.0954 - Training Accuracy: 93.49% | |
| Step [1200/6957] - Training Loss: 0.0639 - Training Accuracy: 93.53% | |
| Step [1300/6957] - Training Loss: 0.2220 - Training Accuracy: 93.53% | |
| Step [1400/6957] - Training Loss: 0.2062 - Training Accuracy: 93.56% | |
| Step [1500/6957] - Training Loss: 0.0326 - Training Accuracy: 93.64% | |
| Step [1600/6957] - Training Loss: 0.2931 - Training Accuracy: 93.66% | |
| Step [1700/6957] - Training Loss: 0.0880 - Training Accuracy: 93.70% | |
| Step [1800/6957] - Training Loss: 0.0241 - Training Accuracy: 93.70% | |
| Step [1900/6957] - Training Loss: 0.0619 - Training Accuracy: 93.71% | |
| Step [2000/6957] - Training Loss: 0.1593 - Training Accuracy: 93.72% | |
| Step [2100/6957] - Training Loss: 0.0890 - Training Accuracy: 93.78% | |
| Step [2200/6957] - Training Loss: 0.1744 - Training Accuracy: 93.82% | |
| Step [2300/6957] - Training Loss: 0.0761 - Training Accuracy: 93.86% | |
| Step [2400/6957] - Training Loss: 0.3924 - Training Accuracy: 93.87% | |
| Step [2500/6957] - Training Loss: 0.2050 - Training Accuracy: 93.86% | |
| Step [2600/6957] - Training Loss: 0.0371 - Training Accuracy: 93.88% | |
| Step [2700/6957] - Training Loss: 0.1727 - Training Accuracy: 93.93% | |
| Step [2800/6957] - Training Loss: 0.0570 - Training Accuracy: 93.95% | |
| Step [2900/6957] - Training Loss: 0.2432 - Training Accuracy: 93.98% | |
| Step [3000/6957] - Training Loss: 0.2299 - Training Accuracy: 94.02% | |
| Step [3100/6957] - Training Loss: 0.3919 - Training Accuracy: 94.03% | |
| Step [3200/6957] - Training Loss: 0.0999 - Training Accuracy: 94.02% | |
| Step [3300/6957] - Training Loss: 0.0287 - Training Accuracy: 94.04% | |
| Step [3400/6957] - Training Loss: 0.1648 - Training Accuracy: 94.06% | |
| Step [3500/6957] - Training Loss: 0.0195 - Training Accuracy: 94.09% | |
| Step [3600/6957] - Training Loss: 0.0116 - Training Accuracy: 94.13% | |
| Step [3700/6957] - Training Loss: 0.1164 - Training Accuracy: 94.15% | |
| Step [3800/6957] - Training Loss: 0.0321 - Training Accuracy: 94.18% | |
| Step [3900/6957] - Training Loss: 0.0655 - Training Accuracy: 94.18% | |
| Step [4000/6957] - Training Loss: 0.1307 - Training Accuracy: 94.16% | |
| Step [4100/6957] - Training Loss: 0.0795 - Training Accuracy: 94.16% | |
| Step [4200/6957] - Training Loss: 0.0091 - Training Accuracy: 94.21% | |
| Step [4300/6957] - Training Loss: 0.4939 - Training Accuracy: 94.23% | |
| Step [4400/6957] - Training Loss: 0.4092 - Training Accuracy: 94.24% | |
| Step [4500/6957] - Training Loss: 0.6429 - Training Accuracy: 94.31% | |
| Step [4600/6957] - Training Loss: 0.0037 - Training Accuracy: 94.32% | |
| Step [4700/6957] - Training Loss: 0.0395 - Training Accuracy: 94.35% | |
| Step [4800/6957] - Training Loss: 0.0951 - Training Accuracy: 94.35% | |
| Step [4900/6957] - Training Loss: 0.0908 - Training Accuracy: 94.35% | |
| Step [5000/6957] - Training Loss: 0.0033 - Training Accuracy: 94.38% | |
| Step [5100/6957] - Training Loss: 0.1262 - Training Accuracy: 94.39% | |
| Step [5200/6957] - Training Loss: 0.0917 - Training Accuracy: 94.42% | |
| Step [5300/6957] - Training Loss: 0.0067 - Training Accuracy: 94.43% | |
| Step [5400/6957] - Training Loss: 0.2684 - Training Accuracy: 94.42% | |
| Step [5500/6957] - Training Loss: 0.1716 - Training Accuracy: 94.42% | |
| Step [5600/6957] - Training Loss: 0.0742 - Training Accuracy: 94.42% | |
| Step [5700/6957] - Training Loss: 0.0271 - Training Accuracy: 94.44% | |
| Step [5800/6957] - Training Loss: 0.1032 - Training Accuracy: 94.45% | |
| Step [5900/6957] - Training Loss: 0.0145 - Training Accuracy: 94.47% | |
| Step [6000/6957] - Training Loss: 0.0142 - Training Accuracy: 94.47% | |
| Step [6100/6957] - Training Loss: 0.3259 - Training Accuracy: 94.47% | |
| Step [6200/6957] - Training Loss: 0.0682 - Training Accuracy: 94.48% | |
| Step [6300/6957] - Training Loss: 0.1334 - Training Accuracy: 94.49% | |
| Step [6400/6957] - Training Loss: 0.0246 - Training Accuracy: 94.50% | |
| Step [6500/6957] - Training Loss: 0.1273 - Training Accuracy: 94.51% | |
| Step [6600/6957] - Training Loss: 0.1915 - Training Accuracy: 94.53% | |
| Step [6700/6957] - Training Loss: 0.0605 - Training Accuracy: 94.56% | |
| Step [6800/6957] - Training Loss: 0.0101 - Training Accuracy: 94.58% | |
| Step [6900/6957] - Training Loss: 0.0102 - Training Accuracy: 94.59% | |
| Epoch [4/20] - Training Loss: 0.1396, Training Accuracy: 94.62% - Validation Loss: 0.8121, Validation Accuracy: 78.37% | |
| Step [100/6957] - Training Loss: 0.1795 - Training Accuracy: 97.56% | |
| Step [200/6957] - Training Loss: 0.0461 - Training Accuracy: 97.03% | |
| Step [300/6957] - Training Loss: 0.0403 - Training Accuracy: 96.77% | |
| Step [400/6957] - Training Loss: 0.0004 - Training Accuracy: 96.72% | |
| Step [500/6957] - Training Loss: 0.1122 - Training Accuracy: 96.62% | |
| Step [600/6957] - Training Loss: 0.1140 - Training Accuracy: 96.67% | |
| Step [700/6957] - Training Loss: 0.0250 - Training Accuracy: 96.54% | |
| Step [800/6957] - Training Loss: 0.0544 - Training Accuracy: 96.49% | |
| Step [900/6957] - Training Loss: 0.0044 - Training Accuracy: 96.44% | |
| Step [1000/6957] - Training Loss: 0.0344 - Training Accuracy: 96.49% | |
| Step [1100/6957] - Training Loss: 0.3842 - Training Accuracy: 96.39% | |
| Step [1200/6957] - Training Loss: 0.0999 - Training Accuracy: 96.36% | |
| Step [1300/6957] - Training Loss: 0.0013 - Training Accuracy: 96.40% | |
| Step [1400/6957] - Training Loss: 0.0196 - Training Accuracy: 96.36% | |
| Step [1500/6957] - Training Loss: 0.0016 - Training Accuracy: 96.44% | |
| Step [1600/6957] - Training Loss: 0.0162 - Training Accuracy: 96.46% | |
| Step [1700/6957] - Training Loss: 0.0282 - Training Accuracy: 96.41% | |
| Step [1800/6957] - Training Loss: 0.0410 - Training Accuracy: 96.40% | |
| Step [1900/6957] - Training Loss: 0.1005 - Training Accuracy: 96.45% | |
| Step [2000/6957] - Training Loss: 0.0843 - Training Accuracy: 96.43% | |
| Step [2100/6957] - Training Loss: 0.3380 - Training Accuracy: 96.40% | |
| Step [2200/6957] - Training Loss: 0.0882 - Training Accuracy: 96.36% | |
| Step [2300/6957] - Training Loss: 0.0401 - Training Accuracy: 96.42% | |
| Step [2400/6957] - Training Loss: 0.0009 - Training Accuracy: 96.45% | |
| Step [2500/6957] - Training Loss: 0.3870 - Training Accuracy: 96.47% | |
| Step [2600/6957] - Training Loss: 0.0423 - Training Accuracy: 96.50% | |
| Step [2700/6957] - Training Loss: 0.0465 - Training Accuracy: 96.47% | |
| Step [2800/6957] - Training Loss: 0.0052 - Training Accuracy: 96.46% | |
| Step [2900/6957] - Training Loss: 0.1293 - Training Accuracy: 96.47% | |
| Step [3000/6957] - Training Loss: 0.0185 - Training Accuracy: 96.46% | |
| Step [3100/6957] - Training Loss: 0.1027 - Training Accuracy: 96.46% | |
| Step [3200/6957] - Training Loss: 0.0345 - Training Accuracy: 96.45% | |
| Step [3300/6957] - Training Loss: 0.0106 - Training Accuracy: 96.46% | |
| Step [3400/6957] - Training Loss: 0.0496 - Training Accuracy: 96.47% | |
| Step [3500/6957] - Training Loss: 0.0083 - Training Accuracy: 96.46% | |
| Step [3600/6957] - Training Loss: 0.0428 - Training Accuracy: 96.48% | |
| Step [3700/6957] - Training Loss: 0.0293 - Training Accuracy: 96.47% | |
| Step [3800/6957] - Training Loss: 0.0272 - Training Accuracy: 96.46% | |
| Step [3900/6957] - Training Loss: 0.0442 - Training Accuracy: 96.46% | |
| Step [4000/6957] - Training Loss: 0.0757 - Training Accuracy: 96.46% | |
| Step [4100/6957] - Training Loss: 0.0468 - Training Accuracy: 96.48% | |
| Step [4200/6957] - Training Loss: 0.2026 - Training Accuracy: 96.53% | |
| Step [4300/6957] - Training Loss: 0.0221 - Training Accuracy: 96.53% | |
| Step [4400/6957] - Training Loss: 0.0253 - Training Accuracy: 96.55% | |
| Step [4500/6957] - Training Loss: 0.0224 - Training Accuracy: 96.55% | |
| Step [4600/6957] - Training Loss: 0.1245 - Training Accuracy: 96.54% | |
| Step [4700/6957] - Training Loss: 0.3774 - Training Accuracy: 96.55% | |
| Step [4800/6957] - Training Loss: 0.0467 - Training Accuracy: 96.53% | |
| Step [4900/6957] - Training Loss: 0.1066 - Training Accuracy: 96.54% | |
| Step [5000/6957] - Training Loss: 0.5417 - Training Accuracy: 96.53% | |
| Step [5100/6957] - Training Loss: 0.2463 - Training Accuracy: 96.53% | |
| Step [5200/6957] - Training Loss: 0.0010 - Training Accuracy: 96.55% | |
| Step [5300/6957] - Training Loss: 0.0147 - Training Accuracy: 96.54% | |
| Step [5400/6957] - Training Loss: 0.0311 - Training Accuracy: 96.57% | |
| Step [5500/6957] - Training Loss: 0.0370 - Training Accuracy: 96.58% | |
| Step [5600/6957] - Training Loss: 0.0706 - Training Accuracy: 96.60% | |
| Step [5700/6957] - Training Loss: 0.1782 - Training Accuracy: 96.62% | |
| Step [5800/6957] - Training Loss: 0.0053 - Training Accuracy: 96.65% | |
| Step [5900/6957] - Training Loss: 0.0070 - Training Accuracy: 96.64% | |
| Step [6000/6957] - Training Loss: 0.0226 - Training Accuracy: 96.65% | |
| Step [6100/6957] - Training Loss: 0.0067 - Training Accuracy: 96.67% | |
| Step [6200/6957] - Training Loss: 0.0129 - Training Accuracy: 96.67% | |
| Step [6300/6957] - Training Loss: 0.0043 - Training Accuracy: 96.66% | |
| Step [6400/6957] - Training Loss: 0.1286 - Training Accuracy: 96.66% | |
| Step [6500/6957] - Training Loss: 0.0056 - Training Accuracy: 96.67% | |
| Step [6600/6957] - Training Loss: 0.0525 - Training Accuracy: 96.68% | |
| Step [6700/6957] - Training Loss: 0.0320 - Training Accuracy: 96.67% | |
| Step [6800/6957] - Training Loss: 0.0019 - Training Accuracy: 96.68% | |
| Step [6900/6957] - Training Loss: 0.0179 - Training Accuracy: 96.69% | |
| Epoch [5/20] - Training Loss: 0.0886, Training Accuracy: 96.68% - Validation Loss: 0.7687, Validation Accuracy: 76.08% | |
| Step [100/6957] - Training Loss: 0.0053 - Training Accuracy: 97.94% | |
| Step [200/6957] - Training Loss: 0.0482 - Training Accuracy: 97.97% | |
| Step [300/6957] - Training Loss: 0.1830 - Training Accuracy: 97.75% | |
| Step [400/6957] - Training Loss: 0.0241 - Training Accuracy: 97.61% | |
| Step [500/6957] - Training Loss: 0.0387 - Training Accuracy: 97.79% | |
| Step [600/6957] - Training Loss: 0.0022 - Training Accuracy: 97.59% | |
| Step [700/6957] - Training Loss: 0.0045 - Training Accuracy: 97.55% | |
| Step [800/6957] - Training Loss: 0.0004 - Training Accuracy: 97.57% | |
| Step [900/6957] - Training Loss: 0.3061 - Training Accuracy: 97.51% | |
| Step [1000/6957] - Training Loss: 0.1072 - Training Accuracy: 97.59% | |
| Step [1100/6957] - Training Loss: 0.0221 - Training Accuracy: 97.56% | |
| Step [1200/6957] - Training Loss: 0.1577 - Training Accuracy: 97.56% | |
| Step [1300/6957] - Training Loss: 0.0118 - Training Accuracy: 97.50% | |
| Step [1400/6957] - Training Loss: 0.0175 - Training Accuracy: 97.54% | |
| Step [1500/6957] - Training Loss: 0.1344 - Training Accuracy: 97.58% | |
| Step [1600/6957] - Training Loss: 0.2380 - Training Accuracy: 97.57% | |
| Step [1700/6957] - Training Loss: 0.0012 - Training Accuracy: 97.65% | |
| Step [1800/6957] - Training Loss: 0.0025 - Training Accuracy: 97.66% | |
| Step [1900/6957] - Training Loss: 0.0156 - Training Accuracy: 97.73% | |
| Step [2000/6957] - Training Loss: 0.0006 - Training Accuracy: 97.70% | |
| Step [2100/6957] - Training Loss: 0.0040 - Training Accuracy: 97.64% | |
| Step [2200/6957] - Training Loss: 0.0039 - Training Accuracy: 97.65% | |
| Step [2300/6957] - Training Loss: 0.0077 - Training Accuracy: 97.66% | |
| Step [2400/6957] - Training Loss: 0.0050 - Training Accuracy: 97.66% | |
| Step [2500/6957] - Training Loss: 0.0577 - Training Accuracy: 97.66% | |
| Step [2600/6957] - Training Loss: 0.0017 - Training Accuracy: 97.65% | |
| Step [2700/6957] - Training Loss: 0.0307 - Training Accuracy: 97.60% | |
| Step [2800/6957] - Training Loss: 0.0219 - Training Accuracy: 97.61% | |
| Step [2900/6957] - Training Loss: 0.0044 - Training Accuracy: 97.61% | |
| Step [3000/6957] - Training Loss: 0.0036 - Training Accuracy: 97.59% | |
| Step [3100/6957] - Training Loss: 0.0427 - Training Accuracy: 97.63% | |
| Step [3200/6957] - Training Loss: 0.0186 - Training Accuracy: 97.64% | |
| Step [3300/6957] - Training Loss: 0.0035 - Training Accuracy: 97.66% | |
| Step [3400/6957] - Training Loss: 0.2917 - Training Accuracy: 97.68% | |
| Step [3500/6957] - Training Loss: 0.0176 - Training Accuracy: 97.65% | |
| Step [3600/6957] - Training Loss: 0.0061 - Training Accuracy: 97.65% | |
| Step [3700/6957] - Training Loss: 0.0168 - Training Accuracy: 97.67% | |
| Step [3800/6957] - Training Loss: 0.0058 - Training Accuracy: 97.66% | |
| Step [3900/6957] - Training Loss: 0.0001 - Training Accuracy: 97.64% | |
| Step [4000/6957] - Training Loss: 0.0075 - Training Accuracy: 97.65% | |
| Step [4100/6957] - Training Loss: 0.0092 - Training Accuracy: 97.67% | |
| Step [4200/6957] - Training Loss: 0.0298 - Training Accuracy: 97.67% | |
| Step [4300/6957] - Training Loss: 0.3427 - Training Accuracy: 97.68% | |
| Step [4400/6957] - Training Loss: 0.0152 - Training Accuracy: 97.68% | |
| Step [4500/6957] - Training Loss: 0.0015 - Training Accuracy: 97.66% | |
| Step [4600/6957] - Training Loss: 0.0599 - Training Accuracy: 97.65% | |
| Step [4700/6957] - Training Loss: 0.0004 - Training Accuracy: 97.65% | |
| Step [4800/6957] - Training Loss: 0.7663 - Training Accuracy: 97.66% | |
| Step [4900/6957] - Training Loss: 0.0015 - Training Accuracy: 97.68% | |
| Step [5000/6957] - Training Loss: 0.0025 - Training Accuracy: 97.69% | |
| Step [5100/6957] - Training Loss: 0.0047 - Training Accuracy: 97.67% | |
| Step [5200/6957] - Training Loss: 0.1195 - Training Accuracy: 97.66% | |
| Step [5300/6957] - Training Loss: 0.0147 - Training Accuracy: 97.66% | |
| Step [5400/6957] - Training Loss: 0.0001 - Training Accuracy: 97.68% | |
| Step [5500/6957] - Training Loss: 0.0156 - Training Accuracy: 97.67% | |
| Step [5600/6957] - Training Loss: 0.0020 - Training Accuracy: 97.68% | |
| Step [5700/6957] - Training Loss: 0.0062 - Training Accuracy: 97.69% | |
| Step [5800/6957] - Training Loss: 0.0291 - Training Accuracy: 97.70% | |
| Step [5900/6957] - Training Loss: 0.0016 - Training Accuracy: 97.70% | |
| Step [6000/6957] - Training Loss: 0.0334 - Training Accuracy: 97.69% | |
| Step [6100/6957] - Training Loss: 0.0139 - Training Accuracy: 97.70% | |
| Step [6200/6957] - Training Loss: 0.0058 - Training Accuracy: 97.72% | |
| Step [6300/6957] - Training Loss: 0.0038 - Training Accuracy: 97.73% | |
| Step [6400/6957] - Training Loss: 0.0026 - Training Accuracy: 97.74% | |
| Step [6500/6957] - Training Loss: 0.0370 - Training Accuracy: 97.75% | |
| Step [6600/6957] - Training Loss: 0.2567 - Training Accuracy: 97.78% | |
| Step [6700/6957] - Training Loss: 0.3551 - Training Accuracy: 97.78% | |
| Step [6800/6957] - Training Loss: 0.1339 - Training Accuracy: 97.78% | |
| Step [6900/6957] - Training Loss: 0.0652 - Training Accuracy: 97.77% | |
| Epoch [6/20] - Training Loss: 0.0620, Training Accuracy: 97.78% - Validation Loss: 1.1391, Validation Accuracy: 72.02% | |
| Step [100/6957] - Training Loss: 0.0067 - Training Accuracy: 98.31% | |
| Step [200/6957] - Training Loss: 0.0194 - Training Accuracy: 98.62% | |
| Step [300/6957] - Training Loss: 0.0087 - Training Accuracy: 98.00% | |
| Step [400/6957] - Training Loss: 0.0782 - Training Accuracy: 98.17% | |
| Step [500/6957] - Training Loss: 0.2211 - Training Accuracy: 98.39% | |
| Step [600/6957] - Training Loss: 0.0055 - Training Accuracy: 98.47% | |
| Step [700/6957] - Training Loss: 0.0087 - Training Accuracy: 98.27% | |
| Step [800/6957] - Training Loss: 0.0013 - Training Accuracy: 98.28% | |
| Step [900/6957] - Training Loss: 0.1984 - Training Accuracy: 98.31% | |
| Step [1000/6957] - Training Loss: 0.0178 - Training Accuracy: 98.31% | |
| Step [1100/6957] - Training Loss: 0.0185 - Training Accuracy: 98.30% | |
| Step [1200/6957] - Training Loss: 0.0369 - Training Accuracy: 98.32% | |
| Step [1300/6957] - Training Loss: 0.0084 - Training Accuracy: 98.35% | |
| Step [1400/6957] - Training Loss: 0.6607 - Training Accuracy: 98.37% | |
| Step [1500/6957] - Training Loss: 0.0136 - Training Accuracy: 98.38% | |
| Step [1600/6957] - Training Loss: 0.0448 - Training Accuracy: 98.34% | |
| Step [1700/6957] - Training Loss: 0.0047 - Training Accuracy: 98.29% | |
| Step [1800/6957] - Training Loss: 0.0061 - Training Accuracy: 98.30% | |
| Step [1900/6957] - Training Loss: 0.0203 - Training Accuracy: 98.32% | |
| Step [2000/6957] - Training Loss: 0.1972 - Training Accuracy: 98.27% | |
| Step [2100/6957] - Training Loss: 0.0046 - Training Accuracy: 98.30% | |
| Step [2200/6957] - Training Loss: 0.0090 - Training Accuracy: 98.29% | |
| Step [2300/6957] - Training Loss: 0.0063 - Training Accuracy: 98.27% | |
| Step [2400/6957] - Training Loss: 0.0020 - Training Accuracy: 98.26% | |
| Step [2500/6957] - Training Loss: 0.0066 - Training Accuracy: 98.26% | |
| Step [2600/6957] - Training Loss: 0.0071 - Training Accuracy: 98.23% | |
| Step [2700/6957] - Training Loss: 0.0071 - Training Accuracy: 98.23% | |
| Step [2800/6957] - Training Loss: 0.0087 - Training Accuracy: 98.27% | |
| Step [2900/6957] - Training Loss: 0.1826 - Training Accuracy: 98.29% | |
| Step [3000/6957] - Training Loss: 0.0001 - Training Accuracy: 98.31% | |
| Step [3100/6957] - Training Loss: 0.0004 - Training Accuracy: 98.31% | |
| Step [3200/6957] - Training Loss: 0.0005 - Training Accuracy: 98.32% | |
| Step [3300/6957] - Training Loss: 0.0044 - Training Accuracy: 98.31% | |
| Step [3400/6957] - Training Loss: 0.0197 - Training Accuracy: 98.29% | |
| Step [3500/6957] - Training Loss: 0.0598 - Training Accuracy: 98.28% | |
| Step [3600/6957] - Training Loss: 0.0125 - Training Accuracy: 98.31% | |
| Step [3700/6957] - Training Loss: 0.0022 - Training Accuracy: 98.29% | |
| Step [3800/6957] - Training Loss: 0.7987 - Training Accuracy: 97.77% | |
| Step [3900/6957] - Training Loss: 0.2152 - Training Accuracy: 97.31% | |
| Step [4000/6957] - Training Loss: 0.4918 - Training Accuracy: 97.20% | |
| Step [4100/6957] - Training Loss: 0.0757 - Training Accuracy: 97.16% | |
| Step [4200/6957] - Training Loss: 0.0033 - Training Accuracy: 97.16% | |
| Step [4300/6957] - Training Loss: 0.0026 - Training Accuracy: 97.18% | |
| Step [4400/6957] - Training Loss: 0.1263 - Training Accuracy: 97.19% | |
| Step [4500/6957] - Training Loss: 0.0086 - Training Accuracy: 97.22% | |
| Step [4600/6957] - Training Loss: 0.0187 - Training Accuracy: 97.25% | |
| Step [4700/6957] - Training Loss: 0.0503 - Training Accuracy: 97.29% | |
| Step [4800/6957] - Training Loss: 0.0061 - Training Accuracy: 97.31% | |
| Step [4900/6957] - Training Loss: 0.0032 - Training Accuracy: 97.34% | |
| Step [5000/6957] - Training Loss: 0.0079 - Training Accuracy: 97.37% | |
| Step [5100/6957] - Training Loss: 0.0089 - Training Accuracy: 97.41% | |
| Step [5200/6957] - Training Loss: 0.0211 - Training Accuracy: 97.43% | |
| Step [5300/6957] - Training Loss: 0.0110 - Training Accuracy: 97.45% | |
| Step [5400/6957] - Training Loss: 0.0004 - Training Accuracy: 97.48% | |
| Step [5500/6957] - Training Loss: 0.0013 - Training Accuracy: 97.51% | |
| Step [5600/6957] - Training Loss: 0.0004 - Training Accuracy: 97.54% | |
| Step [5700/6957] - Training Loss: 0.0058 - Training Accuracy: 97.57% | |
| Step [5800/6957] - Training Loss: 0.3683 - Training Accuracy: 97.58% | |
| Step [5900/6957] - Training Loss: 0.0013 - Training Accuracy: 97.61% | |
| Step [6000/6957] - Training Loss: 0.0003 - Training Accuracy: 97.63% | |
| Step [6100/6957] - Training Loss: 0.1631 - Training Accuracy: 97.66% | |
| Step [6200/6957] - Training Loss: 0.0005 - Training Accuracy: 97.68% | |
| Step [6300/6957] - Training Loss: 0.0014 - Training Accuracy: 97.70% | |
| Step [6400/6957] - Training Loss: 0.0051 - Training Accuracy: 97.71% | |
| Step [6500/6957] - Training Loss: 0.0059 - Training Accuracy: 97.73% | |
| Step [6600/6957] - Training Loss: 0.0045 - Training Accuracy: 97.75% | |
| Step [6700/6957] - Training Loss: 0.0140 - Training Accuracy: 97.77% | |
| Step [6800/6957] - Training Loss: 0.2753 - Training Accuracy: 97.65% | |
| Step [6900/6957] - Training Loss: 0.2403 - Training Accuracy: 97.48% | |
| Epoch [7/20] - Training Loss: 0.0855, Training Accuracy: 97.45% - Validation Loss: 0.6950, Validation Accuracy: 73.97% | |
| Step [100/6957] - Training Loss: 0.0372 - Training Accuracy: 95.44% | |
| Step [200/6957] - Training Loss: 0.7471 - Training Accuracy: 82.22% | |
| Step [300/6957] - Training Loss: 0.6515 - Training Accuracy: 73.77% | |
| Step [400/6957] - Training Loss: 0.9450 - Training Accuracy: 70.38% | |
| Step [500/6957] - Training Loss: 0.6124 - Training Accuracy: 68.74% | |
| Step [600/6957] - Training Loss: 0.6085 - Training Accuracy: 67.58% | |
| Step [700/6957] - Training Loss: 0.7818 - Training Accuracy: 67.01% | |
| Step [800/6957] - Training Loss: 0.7816 - Training Accuracy: 66.20% | |
| Step [900/6957] - Training Loss: 0.5890 - Training Accuracy: 66.29% | |
| Step [1000/6957] - Training Loss: 0.4644 - Training Accuracy: 66.24% | |
| Step [1100/6957] - Training Loss: 0.5820 - Training Accuracy: 66.24% | |
| Step [1200/6957] - Training Loss: 0.7090 - Training Accuracy: 66.49% | |
| Step [1300/6957] - Training Loss: 0.6655 - Training Accuracy: 66.58% | |
| Step [1400/6957] - Training Loss: 0.4868 - Training Accuracy: 66.59% | |
| Step [1500/6957] - Training Loss: 0.5511 - Training Accuracy: 66.65% | |
| Step [1600/6957] - Training Loss: 0.5772 - Training Accuracy: 66.66% | |
| Step [1700/6957] - Training Loss: 0.5209 - Training Accuracy: 66.68% | |
| Step [1800/6957] - Training Loss: 0.6469 - Training Accuracy: 66.77% | |
| Step [1900/6957] - Training Loss: 0.4709 - Training Accuracy: 66.77% | |
| Step [2000/6957] - Training Loss: 0.5342 - Training Accuracy: 66.91% | |
| Step [2100/6957] - Training Loss: 0.5105 - Training Accuracy: 66.96% | |
| Step [2200/6957] - Training Loss: 0.5738 - Training Accuracy: 67.07% | |
| Step [2300/6957] - Training Loss: 0.4945 - Training Accuracy: 67.15% | |
| Step [2400/6957] - Training Loss: 0.7853 - Training Accuracy: 67.19% | |
| Step [2500/6957] - Training Loss: 0.8273 - Training Accuracy: 67.13% | |
| Step [2600/6957] - Training Loss: 0.4710 - Training Accuracy: 67.17% | |
| Step [2700/6957] - Training Loss: 0.5047 - Training Accuracy: 67.19% | |
| Step [2800/6957] - Training Loss: 0.6254 - Training Accuracy: 67.36% | |
| Step [2900/6957] - Training Loss: 0.4677 - Training Accuracy: 67.44% | |
| Step [3000/6957] - Training Loss: 0.3683 - Training Accuracy: 67.53% | |
| Step [3100/6957] - Training Loss: 0.5361 - Training Accuracy: 67.67% | |
| Step [3200/6957] - Training Loss: 0.5224 - Training Accuracy: 67.73% | |
| Step [3300/6957] - Training Loss: 0.5593 - Training Accuracy: 67.76% | |
| Step [3400/6957] - Training Loss: 0.4533 - Training Accuracy: 67.86% | |
| Step [3500/6957] - Training Loss: 0.3712 - Training Accuracy: 67.99% | |
| Step [3600/6957] - Training Loss: 0.4081 - Training Accuracy: 68.02% | |
| Step [3700/6957] - Training Loss: 0.9126 - Training Accuracy: 68.15% | |
| Step [3800/6957] - Training Loss: 0.5032 - Training Accuracy: 68.27% | |
| Step [3900/6957] - Training Loss: 0.5640 - Training Accuracy: 68.40% | |
| Step [4000/6957] - Training Loss: 0.8238 - Training Accuracy: 68.49% | |
| Step [4100/6957] - Training Loss: 0.3531 - Training Accuracy: 68.54% | |
| Step [4200/6957] - Training Loss: 0.4814 - Training Accuracy: 68.67% | |
| Step [4300/6957] - Training Loss: 0.5429 - Training Accuracy: 68.78% | |
| Step [4400/6957] - Training Loss: 0.5412 - Training Accuracy: 68.94% | |
| Step [4500/6957] - Training Loss: 0.2831 - Training Accuracy: 69.08% | |
| Step [4600/6957] - Training Loss: 0.4588 - Training Accuracy: 69.18% | |
| Step [4700/6957] - Training Loss: 0.3233 - Training Accuracy: 69.34% | |
| Step [4800/6957] - Training Loss: 0.5136 - Training Accuracy: 69.40% | |
| Step [4900/6957] - Training Loss: 0.4626 - Training Accuracy: 69.44% | |
| Step [5000/6957] - Training Loss: 0.3835 - Training Accuracy: 69.50% | |
| Step [5100/6957] - Training Loss: 0.4914 - Training Accuracy: 69.54% | |
| Step [5200/6957] - Training Loss: 0.4772 - Training Accuracy: 69.61% | |
| Step [5300/6957] - Training Loss: 0.5434 - Training Accuracy: 69.71% | |
| Step [5400/6957] - Training Loss: 0.5098 - Training Accuracy: 69.75% | |
| Step [5500/6957] - Training Loss: 0.5979 - Training Accuracy: 69.83% | |
| Step [5600/6957] - Training Loss: 0.3227 - Training Accuracy: 69.92% | |
| Step [5700/6957] - Training Loss: 0.3403 - Training Accuracy: 70.03% | |
| Step [5800/6957] - Training Loss: 0.3368 - Training Accuracy: 70.14% | |
| Step [5900/6957] - Training Loss: 0.3135 - Training Accuracy: 70.24% | |
| Step [6000/6957] - Training Loss: 0.2030 - Training Accuracy: 70.48% | |
| Step [6100/6957] - Training Loss: 0.8503 - Training Accuracy: 70.80% | |
| Step [6200/6957] - Training Loss: 0.7200 - Training Accuracy: 70.59% | |
| Step [6300/6957] - Training Loss: 0.5854 - Training Accuracy: 70.48% | |
| Step [6400/6957] - Training Loss: 0.6162 - Training Accuracy: 70.39% | |
| Step [6500/6957] - Training Loss: 0.7088 - Training Accuracy: 70.37% | |
| Step [6600/6957] - Training Loss: 0.5531 - Training Accuracy: 70.36% | |
| Step [6700/6957] - Training Loss: 0.5104 - Training Accuracy: 70.39% | |
| Step [6800/6957] - Training Loss: 0.5390 - Training Accuracy: 70.40% | |
| Step [6900/6957] - Training Loss: 0.2770 - Training Accuracy: 70.44% | |
| Epoch [8/20] - Training Loss: 0.5975, Training Accuracy: 70.43% - Validation Loss: 0.6084, Validation Accuracy: 69.23% | |
| Step [100/6957] - Training Loss: 0.4798 - Training Accuracy: 72.75% | |
| Step [200/6957] - Training Loss: 0.5456 - Training Accuracy: 71.97% | |
| Step [300/6957] - Training Loss: 0.6890 - Training Accuracy: 71.88% | |
| Step [400/6957] - Training Loss: 0.6333 - Training Accuracy: 72.45% | |
| Step [500/6957] - Training Loss: 0.5491 - Training Accuracy: 72.64% | |
| Step [600/6957] - Training Loss: 0.3878 - Training Accuracy: 73.18% | |
| Step [700/6957] - Training Loss: 0.6072 - Training Accuracy: 73.31% | |
| Step [800/6957] - Training Loss: 0.4409 - Training Accuracy: 73.60% | |
| Step [900/6957] - Training Loss: 0.4719 - Training Accuracy: 74.07% | |
| Step [1000/6957] - Training Loss: 0.1930 - Training Accuracy: 74.50% | |
| Step [1100/6957] - Training Loss: 0.5415 - Training Accuracy: 74.91% | |
| Step [1200/6957] - Training Loss: 0.3093 - Training Accuracy: 75.20% | |
| Step [1300/6957] - Training Loss: 0.5559 - Training Accuracy: 75.65% | |
| Step [1400/6957] - Training Loss: 0.3150 - Training Accuracy: 76.21% | |
| Step [1500/6957] - Training Loss: 0.3690 - Training Accuracy: 76.82% | |
| Step [1600/6957] - Training Loss: 0.1253 - Training Accuracy: 77.52% | |
| Step [1700/6957] - Training Loss: 0.3504 - Training Accuracy: 78.38% | |
| Step [1800/6957] - Training Loss: 0.1586 - Training Accuracy: 79.31% | |
| Step [1900/6957] - Training Loss: 0.4286 - Training Accuracy: 79.91% | |
| Step [2000/6957] - Training Loss: 0.2534 - Training Accuracy: 79.86% | |
| Step [2100/6957] - Training Loss: 0.2691 - Training Accuracy: 80.32% | |
| Step [2200/6957] - Training Loss: 0.3364 - Training Accuracy: 80.87% | |
| Step [2300/6957] - Training Loss: 0.0185 - Training Accuracy: 81.52% | |
| Step [2400/6957] - Training Loss: 0.0702 - Training Accuracy: 82.15% | |
| Step [2500/6957] - Training Loss: 0.0358 - Training Accuracy: 82.76% | |
| Step [2600/6957] - Training Loss: 0.0221 - Training Accuracy: 83.32% | |
| Step [2700/6957] - Training Loss: 0.0342 - Training Accuracy: 83.88% | |
| Step [2800/6957] - Training Loss: 0.0023 - Training Accuracy: 84.41% | |
| Step [2900/6957] - Training Loss: 0.0068 - Training Accuracy: 84.89% | |
| Step [3000/6957] - Training Loss: 0.0466 - Training Accuracy: 85.36% | |
| Step [3100/6957] - Training Loss: 0.0003 - Training Accuracy: 85.82% | |
| Step [3200/6957] - Training Loss: 0.0379 - Training Accuracy: 86.23% | |
| Step [3300/6957] - Training Loss: 0.0261 - Training Accuracy: 86.61% | |
| Step [3400/6957] - Training Loss: 0.0019 - Training Accuracy: 86.97% | |
| Step [3500/6957] - Training Loss: 0.0018 - Training Accuracy: 87.32% | |
| Step [3600/6957] - Training Loss: 0.0003 - Training Accuracy: 87.65% | |
| Step [3700/6957] - Training Loss: 0.0004 - Training Accuracy: 87.96% | |
| Step [3800/6957] - Training Loss: 0.0024 - Training Accuracy: 88.26% | |
| Step [3900/6957] - Training Loss: 0.0153 - Training Accuracy: 88.54% | |
| Step [4000/6957] - Training Loss: 0.0009 - Training Accuracy: 88.81% | |
| Step [4100/6957] - Training Loss: 0.0037 - Training Accuracy: 89.07% | |
| Step [4200/6957] - Training Loss: 0.0006 - Training Accuracy: 89.31% | |
| Step [4300/6957] - Training Loss: 0.0001 - Training Accuracy: 89.54% | |
| Step [4400/6957] - Training Loss: 0.0006 - Training Accuracy: 89.76% | |
| Step [4500/6957] - Training Loss: 0.0005 - Training Accuracy: 89.96% | |
| Step [4600/6957] - Training Loss: 0.0002 - Training Accuracy: 90.16% | |
| Step [4700/6957] - Training Loss: 0.0031 - Training Accuracy: 90.35% | |
| Step [4800/6957] - Training Loss: 0.0002 - Training Accuracy: 90.54% | |
| Step [4900/6957] - Training Loss: 0.0008 - Training Accuracy: 90.72% | |
| Step [5000/6957] - Training Loss: 0.0170 - Training Accuracy: 90.89% | |
| Step [5100/6957] - Training Loss: 0.0093 - Training Accuracy: 91.04% | |
| Step [5200/6957] - Training Loss: 0.0000 - Training Accuracy: 91.21% | |
| Step [5300/6957] - Training Loss: 0.0058 - Training Accuracy: 91.37% | |
| Step [5400/6957] - Training Loss: 0.0038 - Training Accuracy: 91.49% | |
| Step [5500/6957] - Training Loss: 0.0124 - Training Accuracy: 91.62% | |
| Step [5600/6957] - Training Loss: 0.0002 - Training Accuracy: 91.75% | |
| Step [5700/6957] - Training Loss: 0.1484 - Training Accuracy: 91.89% | |
| Step [5800/6957] - Training Loss: 0.0030 - Training Accuracy: 92.02% | |
| Step [5900/6957] - Training Loss: 0.1941 - Training Accuracy: 92.14% | |
| Step [6000/6957] - Training Loss: 0.1760 - Training Accuracy: 92.26% | |
| Step [6100/6957] - Training Loss: 0.0090 - Training Accuracy: 92.37% | |
| Step [6200/6957] - Training Loss: 0.3569 - Training Accuracy: 92.48% | |
| Step [6300/6957] - Training Loss: 0.0101 - Training Accuracy: 92.58% | |
| Step [6400/6957] - Training Loss: 0.1208 - Training Accuracy: 92.69% | |
| Step [6500/6957] - Training Loss: 0.0064 - Training Accuracy: 92.77% | |
| Step [6600/6957] - Training Loss: 0.0005 - Training Accuracy: 92.86% | |
| Step [6700/6957] - Training Loss: 0.0004 - Training Accuracy: 92.95% | |
| Step [6800/6957] - Training Loss: 0.0013 - Training Accuracy: 93.04% | |
| Step [6900/6957] - Training Loss: 0.1766 - Training Accuracy: 93.12% | |
| Epoch [9/20] - Training Loss: 0.1502, Training Accuracy: 93.17% - Validation Loss: 1.0563, Validation Accuracy: 77.98% | |
| Step [100/6957] - Training Loss: 0.0011 - Training Accuracy: 99.06% | |
| Step [200/6957] - Training Loss: 0.0255 - Training Accuracy: 99.22% | |
| Step [300/6957] - Training Loss: 0.0121 - Training Accuracy: 99.21% | |
| Step [400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.25% | |
| Step [500/6957] - Training Loss: 0.0018 - Training Accuracy: 99.17% | |
| Step [600/6957] - Training Loss: 0.0002 - Training Accuracy: 99.12% | |
| Step [700/6957] - Training Loss: 0.0035 - Training Accuracy: 99.10% | |
| Step [800/6957] - Training Loss: 0.0007 - Training Accuracy: 99.12% | |
| Step [900/6957] - Training Loss: 0.0404 - Training Accuracy: 99.09% | |
| Step [1000/6957] - Training Loss: 0.0001 - Training Accuracy: 99.06% | |
| Step [1100/6957] - Training Loss: 0.0002 - Training Accuracy: 98.99% | |
| Step [1200/6957] - Training Loss: 0.0009 - Training Accuracy: 99.04% | |
| Step [1300/6957] - Training Loss: 0.0010 - Training Accuracy: 99.06% | |
| Step [1400/6957] - Training Loss: 0.0117 - Training Accuracy: 99.07% | |
| Step [1500/6957] - Training Loss: 0.0065 - Training Accuracy: 99.08% | |
| Step [1600/6957] - Training Loss: 0.0003 - Training Accuracy: 99.11% | |
| Step [1700/6957] - Training Loss: 0.0066 - Training Accuracy: 99.14% | |
| Step [1800/6957] - Training Loss: 0.0006 - Training Accuracy: 99.11% | |
| Step [1900/6957] - Training Loss: 0.5156 - Training Accuracy: 99.07% | |
| Step [2000/6957] - Training Loss: 0.1773 - Training Accuracy: 99.03% | |
| Step [2100/6957] - Training Loss: 0.0027 - Training Accuracy: 99.02% | |
| Step [2200/6957] - Training Loss: 0.0250 - Training Accuracy: 99.02% | |
| Step [2300/6957] - Training Loss: 0.0011 - Training Accuracy: 99.00% | |
| Step [2400/6957] - Training Loss: 0.0577 - Training Accuracy: 99.00% | |
| Step [2500/6957] - Training Loss: 0.0001 - Training Accuracy: 99.00% | |
| Step [2600/6957] - Training Loss: 0.0258 - Training Accuracy: 99.01% | |
| Step [2700/6957] - Training Loss: 0.0016 - Training Accuracy: 99.03% | |
| Step [2800/6957] - Training Loss: 0.0002 - Training Accuracy: 99.03% | |
| Step [2900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.02% | |
| Step [3000/6957] - Training Loss: 0.0001 - Training Accuracy: 99.03% | |
| Step [3100/6957] - Training Loss: 0.0004 - Training Accuracy: 99.02% | |
| Step [3200/6957] - Training Loss: 0.0006 - Training Accuracy: 99.04% | |
| Step [3300/6957] - Training Loss: 0.0000 - Training Accuracy: 99.05% | |
| Step [3400/6957] - Training Loss: 0.0004 - Training Accuracy: 99.05% | |
| Step [3500/6957] - Training Loss: 0.0001 - Training Accuracy: 99.06% | |
| Step [3600/6957] - Training Loss: 0.0016 - Training Accuracy: 99.05% | |
| Step [3700/6957] - Training Loss: 0.0023 - Training Accuracy: 99.05% | |
| Step [3800/6957] - Training Loss: 0.0052 - Training Accuracy: 99.04% | |
| Step [3900/6957] - Training Loss: 0.0132 - Training Accuracy: 99.04% | |
| Step [4000/6957] - Training Loss: 0.0029 - Training Accuracy: 99.05% | |
| Step [4100/6957] - Training Loss: 0.0002 - Training Accuracy: 99.06% | |
| Step [4200/6957] - Training Loss: 0.0350 - Training Accuracy: 99.07% | |
| Step [4300/6957] - Training Loss: 0.0055 - Training Accuracy: 99.08% | |
| Step [4400/6957] - Training Loss: 0.0158 - Training Accuracy: 99.09% | |
| Step [4500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.09% | |
| Step [4600/6957] - Training Loss: 0.0037 - Training Accuracy: 99.08% | |
| Step [4700/6957] - Training Loss: 0.0004 - Training Accuracy: 99.06% | |
| Step [4800/6957] - Training Loss: 0.0498 - Training Accuracy: 99.07% | |
| Step [4900/6957] - Training Loss: 0.0110 - Training Accuracy: 99.07% | |
| Step [5000/6957] - Training Loss: 0.0071 - Training Accuracy: 99.07% | |
| Step [5100/6957] - Training Loss: 0.0025 - Training Accuracy: 99.07% | |
| Step [5200/6957] - Training Loss: 0.0016 - Training Accuracy: 99.08% | |
| Step [5300/6957] - Training Loss: 0.0851 - Training Accuracy: 99.08% | |
| Step [5400/6957] - Training Loss: 0.0015 - Training Accuracy: 99.08% | |
| Step [5500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.08% | |
| Step [5600/6957] - Training Loss: 0.0099 - Training Accuracy: 99.07% | |
| Step [5700/6957] - Training Loss: 0.0001 - Training Accuracy: 99.08% | |
| Step [5800/6957] - Training Loss: 0.0210 - Training Accuracy: 99.09% | |
| Step [5900/6957] - Training Loss: 0.0001 - Training Accuracy: 99.09% | |
| Step [6000/6957] - Training Loss: 0.0000 - Training Accuracy: 99.10% | |
| Step [6100/6957] - Training Loss: 0.0006 - Training Accuracy: 99.11% | |
| Step [6200/6957] - Training Loss: 0.0051 - Training Accuracy: 99.12% | |
| Step [6300/6957] - Training Loss: 0.0022 - Training Accuracy: 99.12% | |
| Step [6400/6957] - Training Loss: 0.0011 - Training Accuracy: 99.11% | |
| Step [6500/6957] - Training Loss: 0.0002 - Training Accuracy: 99.11% | |
| Step [6600/6957] - Training Loss: 0.0003 - Training Accuracy: 99.11% | |
| Step [6700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.12% | |
| Step [6800/6957] - Training Loss: 0.0047 - Training Accuracy: 99.13% | |
| Step [6900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.14% | |
| Epoch [10/20] - Training Loss: 0.0255, Training Accuracy: 99.13% - Validation Loss: 1.1007, Validation Accuracy: 77.30% | |
| Step [100/6957] - Training Loss: 0.0001 - Training Accuracy: 99.62% | |
| Step [200/6957] - Training Loss: 0.0197 - Training Accuracy: 99.50% | |
| Step [300/6957] - Training Loss: 0.0106 - Training Accuracy: 99.35% | |
| Step [400/6957] - Training Loss: 0.0014 - Training Accuracy: 99.38% | |
| Step [500/6957] - Training Loss: 0.0001 - Training Accuracy: 99.42% | |
| Step [600/6957] - Training Loss: 0.0034 - Training Accuracy: 99.36% | |
| Step [700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.35% | |
| Step [800/6957] - Training Loss: 0.0002 - Training Accuracy: 99.27% | |
| Step [900/6957] - Training Loss: 0.0048 - Training Accuracy: 99.28% | |
| Step [1000/6957] - Training Loss: 0.0000 - Training Accuracy: 99.28% | |
| Step [1100/6957] - Training Loss: 0.0024 - Training Accuracy: 99.24% | |
| Step [1200/6957] - Training Loss: 0.0006 - Training Accuracy: 99.27% | |
| Step [1300/6957] - Training Loss: 0.0314 - Training Accuracy: 99.28% | |
| Step [1400/6957] - Training Loss: 0.0001 - Training Accuracy: 99.27% | |
| Step [1500/6957] - Training Loss: 0.0002 - Training Accuracy: 99.29% | |
| Step [1600/6957] - Training Loss: 0.0005 - Training Accuracy: 99.32% | |
| Step [1700/6957] - Training Loss: 0.0216 - Training Accuracy: 99.28% | |
| Step [1800/6957] - Training Loss: 0.0002 - Training Accuracy: 99.28% | |
| Step [1900/6957] - Training Loss: 0.0002 - Training Accuracy: 99.31% | |
| Step [2000/6957] - Training Loss: 0.0003 - Training Accuracy: 99.31% | |
| Step [2100/6957] - Training Loss: 0.0076 - Training Accuracy: 99.31% | |
| Step [2200/6957] - Training Loss: 0.0002 - Training Accuracy: 99.30% | |
| Step [2300/6957] - Training Loss: 0.0002 - Training Accuracy: 99.30% | |
| Step [2400/6957] - Training Loss: 0.0007 - Training Accuracy: 99.31% | |
| Step [2500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.33% | |
| Step [2600/6957] - Training Loss: 0.0002 - Training Accuracy: 99.34% | |
| Step [2700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.37% | |
| Step [2800/6957] - Training Loss: 0.0012 - Training Accuracy: 99.36% | |
| Step [2900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.38% | |
| Step [3000/6957] - Training Loss: 0.0122 - Training Accuracy: 99.37% | |
| Step [3100/6957] - Training Loss: 0.0003 - Training Accuracy: 99.37% | |
| Step [3200/6957] - Training Loss: 0.0003 - Training Accuracy: 99.37% | |
| Step [3300/6957] - Training Loss: 0.0152 - Training Accuracy: 99.39% | |
| Step [3400/6957] - Training Loss: 0.0001 - Training Accuracy: 99.40% | |
| Step [3500/6957] - Training Loss: 0.0303 - Training Accuracy: 99.37% | |
| Step [3600/6957] - Training Loss: 0.0270 - Training Accuracy: 99.38% | |
| Step [3700/6957] - Training Loss: 0.0964 - Training Accuracy: 99.38% | |
| Step [3800/6957] - Training Loss: 0.0106 - Training Accuracy: 99.37% | |
| Step [3900/6957] - Training Loss: 0.0004 - Training Accuracy: 99.37% | |
| Step [4000/6957] - Training Loss: 0.0491 - Training Accuracy: 99.36% | |
| Step [4100/6957] - Training Loss: 0.0008 - Training Accuracy: 99.37% | |
| Step [4200/6957] - Training Loss: 0.0003 - Training Accuracy: 99.37% | |
| Step [4300/6957] - Training Loss: 0.0001 - Training Accuracy: 99.36% | |
| Step [4400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.37% | |
| Step [4500/6957] - Training Loss: 0.0001 - Training Accuracy: 99.38% | |
| Step [4600/6957] - Training Loss: 0.0038 - Training Accuracy: 99.36% | |
| Step [4700/6957] - Training Loss: 0.0012 - Training Accuracy: 99.37% | |
| Step [4800/6957] - Training Loss: 0.0008 - Training Accuracy: 99.36% | |
| Step [4900/6957] - Training Loss: 0.0006 - Training Accuracy: 99.35% | |
| Step [5000/6957] - Training Loss: 0.0005 - Training Accuracy: 99.36% | |
| Step [5100/6957] - Training Loss: 0.0002 - Training Accuracy: 99.37% | |
| Step [5200/6957] - Training Loss: 0.0000 - Training Accuracy: 99.36% | |
| Step [5300/6957] - Training Loss: 0.0080 - Training Accuracy: 99.36% | |
| Step [5400/6957] - Training Loss: 0.0006 - Training Accuracy: 99.37% | |
| Step [5500/6957] - Training Loss: 0.1522 - Training Accuracy: 99.37% | |
| Step [5600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.38% | |
| Step [5700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.38% | |
| Step [5800/6957] - Training Loss: 0.0000 - Training Accuracy: 99.39% | |
| Step [5900/6957] - Training Loss: 0.0001 - Training Accuracy: 99.39% | |
| Step [6000/6957] - Training Loss: 0.0002 - Training Accuracy: 99.39% | |
| Step [6100/6957] - Training Loss: 0.0037 - Training Accuracy: 99.38% | |
| Step [6200/6957] - Training Loss: 0.0062 - Training Accuracy: 99.38% | |
| Step [6300/6957] - Training Loss: 0.0158 - Training Accuracy: 99.38% | |
| Step [6400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.38% | |
| Step [6500/6957] - Training Loss: 0.0006 - Training Accuracy: 99.38% | |
| Step [6600/6957] - Training Loss: 0.0010 - Training Accuracy: 99.39% | |
| Step [6700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.39% | |
| Step [6800/6957] - Training Loss: 0.0055 - Training Accuracy: 99.39% | |
| Step [6900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.40% | |
| Epoch [11/20] - Training Loss: 0.0175, Training Accuracy: 99.40% - Validation Loss: 1.1643, Validation Accuracy: 78.98% | |
| Step [100/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [200/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [300/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.94% | |
| Step [500/6957] - Training Loss: 0.0001 - Training Accuracy: 99.81% | |
| Step [600/6957] - Training Loss: 0.0002 - Training Accuracy: 99.75% | |
| Step [700/6957] - Training Loss: 0.0009 - Training Accuracy: 99.70% | |
| Step [800/6957] - Training Loss: 0.0000 - Training Accuracy: 99.68% | |
| Step [900/6957] - Training Loss: 0.0043 - Training Accuracy: 99.67% | |
| Step [1000/6957] - Training Loss: 0.0011 - Training Accuracy: 99.65% | |
| Step [1100/6957] - Training Loss: 0.0002 - Training Accuracy: 99.65% | |
| Step [1200/6957] - Training Loss: 0.0000 - Training Accuracy: 99.66% | |
| Step [1300/6957] - Training Loss: 0.0005 - Training Accuracy: 99.64% | |
| Step [1400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.62% | |
| Step [1500/6957] - Training Loss: 0.0063 - Training Accuracy: 99.60% | |
| Step [1600/6957] - Training Loss: 0.0002 - Training Accuracy: 99.58% | |
| Step [1700/6957] - Training Loss: 0.0003 - Training Accuracy: 99.58% | |
| Step [1800/6957] - Training Loss: 0.0004 - Training Accuracy: 99.59% | |
| Step [1900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.59% | |
| Step [2000/6957] - Training Loss: 0.0009 - Training Accuracy: 99.60% | |
| Step [2100/6957] - Training Loss: 0.0021 - Training Accuracy: 99.57% | |
| Step [2200/6957] - Training Loss: 0.0217 - Training Accuracy: 99.56% | |
| Step [2300/6957] - Training Loss: 0.0001 - Training Accuracy: 99.56% | |
| Step [2400/6957] - Training Loss: 0.0001 - Training Accuracy: 99.57% | |
| Step [2500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.56% | |
| Step [2600/6957] - Training Loss: 0.0002 - Training Accuracy: 99.56% | |
| Step [2700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.58% | |
| Step [2800/6957] - Training Loss: 0.0002 - Training Accuracy: 99.58% | |
| Step [2900/6957] - Training Loss: 0.0001 - Training Accuracy: 99.60% | |
| Step [3000/6957] - Training Loss: 0.0003 - Training Accuracy: 99.60% | |
| Step [3100/6957] - Training Loss: 0.0004 - Training Accuracy: 99.60% | |
| Step [3200/6957] - Training Loss: 0.0000 - Training Accuracy: 99.61% | |
| Step [3300/6957] - Training Loss: 0.0153 - Training Accuracy: 99.61% | |
| Step [3400/6957] - Training Loss: 0.0065 - Training Accuracy: 99.60% | |
| Step [3500/6957] - Training Loss: 0.0002 - Training Accuracy: 99.59% | |
| Step [3600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.60% | |
| Step [3700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.61% | |
| Step [3800/6957] - Training Loss: 0.0000 - Training Accuracy: 99.62% | |
| Step [3900/6957] - Training Loss: 0.0888 - Training Accuracy: 99.62% | |
| Step [4000/6957] - Training Loss: 0.0029 - Training Accuracy: 99.61% | |
| Step [4100/6957] - Training Loss: 0.0022 - Training Accuracy: 99.61% | |
| Step [4200/6957] - Training Loss: 0.2933 - Training Accuracy: 99.60% | |
| Step [4300/6957] - Training Loss: 0.0000 - Training Accuracy: 99.61% | |
| Step [4400/6957] - Training Loss: 0.2437 - Training Accuracy: 99.61% | |
| Step [4500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.62% | |
| Step [4600/6957] - Training Loss: 0.2120 - Training Accuracy: 99.61% | |
| Step [4700/6957] - Training Loss: 0.0012 - Training Accuracy: 99.61% | |
| Step [4800/6957] - Training Loss: 0.0006 - Training Accuracy: 99.62% | |
| Step [4900/6957] - Training Loss: 0.0001 - Training Accuracy: 99.62% | |
| Step [5000/6957] - Training Loss: 0.0695 - Training Accuracy: 99.61% | |
| Step [5100/6957] - Training Loss: 0.0000 - Training Accuracy: 99.61% | |
| Step [5200/6957] - Training Loss: 0.0000 - Training Accuracy: 99.61% | |
| Step [5300/6957] - Training Loss: 0.0000 - Training Accuracy: 99.62% | |
| Step [5400/6957] - Training Loss: 0.0010 - Training Accuracy: 99.62% | |
| Step [5500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.61% | |
| Step [5600/6957] - Training Loss: 0.0004 - Training Accuracy: 99.61% | |
| Step [5700/6957] - Training Loss: 0.0001 - Training Accuracy: 99.61% | |
| Step [5800/6957] - Training Loss: 0.0001 - Training Accuracy: 99.62% | |
| Step [5900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.61% | |
| Step [6000/6957] - Training Loss: 0.0001 - Training Accuracy: 99.61% | |
| Step [6100/6957] - Training Loss: 0.0012 - Training Accuracy: 99.61% | |
| Step [6200/6957] - Training Loss: 0.0002 - Training Accuracy: 99.61% | |
| Step [6300/6957] - Training Loss: 0.0003 - Training Accuracy: 99.61% | |
| Step [6400/6957] - Training Loss: 0.0002 - Training Accuracy: 99.60% | |
| Step [6500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.60% | |
| Step [6600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.60% | |
| Step [6700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.61% | |
| Step [6800/6957] - Training Loss: 0.0038 - Training Accuracy: 99.61% | |
| Step [6900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.62% | |
| Epoch [12/20] - Training Loss: 0.0113, Training Accuracy: 99.62% - Validation Loss: 1.1339, Validation Accuracy: 76.36% | |
| Step [100/6957] - Training Loss: 0.0001 - Training Accuracy: 99.69% | |
| Step [200/6957] - Training Loss: 0.0000 - Training Accuracy: 99.66% | |
| Step [300/6957] - Training Loss: 0.0000 - Training Accuracy: 99.58% | |
| Step [400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.69% | |
| Step [500/6957] - Training Loss: 0.0001 - Training Accuracy: 99.75% | |
| Step [600/6957] - Training Loss: 0.0001 - Training Accuracy: 99.78% | |
| Step [700/6957] - Training Loss: 0.0010 - Training Accuracy: 99.72% | |
| Step [800/6957] - Training Loss: 0.0000 - Training Accuracy: 99.73% | |
| Step [900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.75% | |
| Step [1000/6957] - Training Loss: 0.0001 - Training Accuracy: 99.76% | |
| Step [1100/6957] - Training Loss: 0.0001 - Training Accuracy: 99.78% | |
| Step [1200/6957] - Training Loss: 0.0000 - Training Accuracy: 99.80% | |
| Step [1300/6957] - Training Loss: 0.0000 - Training Accuracy: 99.80% | |
| Step [1400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.79% | |
| Step [1500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.79% | |
| Step [1600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.79% | |
| Step [1700/6957] - Training Loss: 0.0003 - Training Accuracy: 99.79% | |
| Step [1800/6957] - Training Loss: 0.0027 - Training Accuracy: 99.78% | |
| Step [1900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.79% | |
| Step [2000/6957] - Training Loss: 0.0000 - Training Accuracy: 99.78% | |
| Step [2100/6957] - Training Loss: 0.0086 - Training Accuracy: 99.75% | |
| Step [2200/6957] - Training Loss: 0.0000 - Training Accuracy: 99.76% | |
| Step [2300/6957] - Training Loss: 0.0036 - Training Accuracy: 99.74% | |
| Step [2400/6957] - Training Loss: 0.0001 - Training Accuracy: 99.74% | |
| Step [2500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.75% | |
| Step [2600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.75% | |
| Step [2700/6957] - Training Loss: 0.0168 - Training Accuracy: 99.75% | |
| Step [2800/6957] - Training Loss: 0.0015 - Training Accuracy: 99.75% | |
| Step [2900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.76% | |
| Step [3000/6957] - Training Loss: 0.0092 - Training Accuracy: 99.74% | |
| Step [3100/6957] - Training Loss: 0.0000 - Training Accuracy: 99.74% | |
| Step [3200/6957] - Training Loss: 0.0000 - Training Accuracy: 99.74% | |
| Step [3300/6957] - Training Loss: 0.0000 - Training Accuracy: 99.75% | |
| Step [3400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.75% | |
| Step [3500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.76% | |
| Step [3600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.76% | |
| Step [3700/6957] - Training Loss: 0.0002 - Training Accuracy: 99.76% | |
| Step [3800/6957] - Training Loss: 0.0006 - Training Accuracy: 99.75% | |
| Step [3900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.75% | |
| Step [4000/6957] - Training Loss: 0.0001 - Training Accuracy: 99.75% | |
| Step [4100/6957] - Training Loss: 0.0011 - Training Accuracy: 99.75% | |
| Step [4200/6957] - Training Loss: 0.0000 - Training Accuracy: 99.75% | |
| Step [4300/6957] - Training Loss: 0.0000 - Training Accuracy: 99.76% | |
| Step [4400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.76% | |
| Step [4500/6957] - Training Loss: 0.0003 - Training Accuracy: 99.76% | |
| Step [4600/6957] - Training Loss: 0.0097 - Training Accuracy: 99.76% | |
| Step [4700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.76% | |
| Step [4800/6957] - Training Loss: 0.0002 - Training Accuracy: 99.76% | |
| Step [4900/6957] - Training Loss: 0.0088 - Training Accuracy: 99.76% | |
| Step [5000/6957] - Training Loss: 0.0000 - Training Accuracy: 99.76% | |
| Step [5100/6957] - Training Loss: 0.0001 - Training Accuracy: 99.76% | |
| Step [5200/6957] - Training Loss: 0.0304 - Training Accuracy: 99.77% | |
| Step [5300/6957] - Training Loss: 0.0000 - Training Accuracy: 99.77% | |
| Step [5400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.77% | |
| Step [5500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.78% | |
| Step [5600/6957] - Training Loss: 0.0002 - Training Accuracy: 99.77% | |
| Step [5700/6957] - Training Loss: 0.0001 - Training Accuracy: 99.78% | |
| Step [5800/6957] - Training Loss: 0.0000 - Training Accuracy: 99.77% | |
| Step [5900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.78% | |
| Step [6000/6957] - Training Loss: 0.2776 - Training Accuracy: 99.78% | |
| Step [6100/6957] - Training Loss: 0.0001 - Training Accuracy: 99.78% | |
| Step [6200/6957] - Training Loss: 0.0000 - Training Accuracy: 99.78% | |
| Step [6300/6957] - Training Loss: 0.0001 - Training Accuracy: 99.77% | |
| Step [6400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.77% | |
| Step [6500/6957] - Training Loss: 0.0001 - Training Accuracy: 99.77% | |
| Step [6600/6957] - Training Loss: 0.0101 - Training Accuracy: 99.77% | |
| Step [6700/6957] - Training Loss: 0.0326 - Training Accuracy: 99.77% | |
| Step [6800/6957] - Training Loss: 0.0001 - Training Accuracy: 99.77% | |
| Step [6900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.78% | |
| Epoch [13/20] - Training Loss: 0.0072, Training Accuracy: 99.78% - Validation Loss: 1.1779, Validation Accuracy: 79.64% | |
| Step [100/6957] - Training Loss: 0.0001 - Training Accuracy: 99.81% | |
| Step [200/6957] - Training Loss: 0.0000 - Training Accuracy: 99.78% | |
| Step [300/6957] - Training Loss: 0.0000 - Training Accuracy: 99.77% | |
| Step [400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.80% | |
| Step [500/6957] - Training Loss: 0.0001 - Training Accuracy: 99.80% | |
| Step [600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.83% | |
| Step [700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.84% | |
| Step [800/6957] - Training Loss: 0.0016 - Training Accuracy: 99.80% | |
| Step [900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.82% | |
| Step [1000/6957] - Training Loss: 0.0000 - Training Accuracy: 99.83% | |
| Step [1100/6957] - Training Loss: 0.0034 - Training Accuracy: 99.84% | |
| Step [1200/6957] - Training Loss: 0.0000 - Training Accuracy: 99.85% | |
| Step [1300/6957] - Training Loss: 0.0000 - Training Accuracy: 99.86% | |
| Step [1400/6957] - Training Loss: 0.0001 - Training Accuracy: 99.85% | |
| Step [1500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.83% | |
| Step [1600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.82% | |
| Step [1700/6957] - Training Loss: 0.0001 - Training Accuracy: 99.81% | |
| Step [1800/6957] - Training Loss: 0.0004 - Training Accuracy: 99.82% | |
| Step [1900/6957] - Training Loss: 0.0001 - Training Accuracy: 99.83% | |
| Step [2000/6957] - Training Loss: 0.0000 - Training Accuracy: 99.83% | |
| Step [2100/6957] - Training Loss: 0.0001 - Training Accuracy: 99.84% | |
| Step [2200/6957] - Training Loss: 0.0031 - Training Accuracy: 99.84% | |
| Step [2300/6957] - Training Loss: 0.0001 - Training Accuracy: 99.85% | |
| Step [2400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.85% | |
| Step [2500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.85% | |
| Step [2600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.85% | |
| Step [2700/6957] - Training Loss: 0.0005 - Training Accuracy: 99.84% | |
| Step [2800/6957] - Training Loss: 0.0000 - Training Accuracy: 99.85% | |
| Step [2900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.85% | |
| Step [3000/6957] - Training Loss: 0.0001 - Training Accuracy: 99.85% | |
| Step [3100/6957] - Training Loss: 0.0001 - Training Accuracy: 99.85% | |
| Step [3200/6957] - Training Loss: 0.0042 - Training Accuracy: 99.85% | |
| Step [3300/6957] - Training Loss: 0.0001 - Training Accuracy: 99.84% | |
| Step [3400/6957] - Training Loss: 0.0004 - Training Accuracy: 99.84% | |
| Step [3500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.85% | |
| Step [3600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.85% | |
| Step [3700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.85% | |
| Step [3800/6957] - Training Loss: 0.0011 - Training Accuracy: 99.86% | |
| Step [3900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.85% | |
| Step [4000/6957] - Training Loss: 0.0000 - Training Accuracy: 99.85% | |
| Step [4100/6957] - Training Loss: 0.0000 - Training Accuracy: 99.85% | |
| Step [4200/6957] - Training Loss: 0.0000 - Training Accuracy: 99.85% | |
| Step [4300/6957] - Training Loss: 0.0130 - Training Accuracy: 99.85% | |
| Step [4400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.85% | |
| Step [4500/6957] - Training Loss: 0.0002 - Training Accuracy: 99.85% | |
| Step [4600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.85% | |
| Step [4700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.86% | |
| Step [4800/6957] - Training Loss: 0.0000 - Training Accuracy: 99.86% | |
| Step [4900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.86% | |
| Step [5000/6957] - Training Loss: 0.0000 - Training Accuracy: 99.86% | |
| Step [5100/6957] - Training Loss: 0.0007 - Training Accuracy: 99.86% | |
| Step [5200/6957] - Training Loss: 0.0000 - Training Accuracy: 99.86% | |
| Step [5300/6957] - Training Loss: 0.0000 - Training Accuracy: 99.85% | |
| Step [5400/6957] - Training Loss: 0.0040 - Training Accuracy: 99.85% | |
| Step [5500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.86% | |
| Step [5600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.86% | |
| Step [5700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.86% | |
| Step [5800/6957] - Training Loss: 0.0000 - Training Accuracy: 99.86% | |
| Step [5900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.86% | |
| Step [6000/6957] - Training Loss: 0.0000 - Training Accuracy: 99.86% | |
| Step [6100/6957] - Training Loss: 0.0000 - Training Accuracy: 99.86% | |
| Step [6200/6957] - Training Loss: 0.0002 - Training Accuracy: 99.86% | |
| Step [6300/6957] - Training Loss: 0.0001 - Training Accuracy: 99.86% | |
| Step [6400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.86% | |
| Step [6500/6957] - Training Loss: 0.0001 - Training Accuracy: 99.86% | |
| Step [6600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.86% | |
| Step [6700/6957] - Training Loss: 0.0002 - Training Accuracy: 99.86% | |
| Step [6800/6957] - Training Loss: 0.0000 - Training Accuracy: 99.86% | |
| Step [6900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.87% | |
| Epoch [14/20] - Training Loss: 0.0044, Training Accuracy: 99.87% - Validation Loss: 1.3142, Validation Accuracy: 80.57% | |
| Step [100/6957] - Training Loss: 0.0000 - Training Accuracy: 99.88% | |
| Step [200/6957] - Training Loss: 0.0000 - Training Accuracy: 99.94% | |
| Step [300/6957] - Training Loss: 0.0000 - Training Accuracy: 99.96% | |
| Step [400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [500/6957] - Training Loss: 0.0001 - Training Accuracy: 99.97% | |
| Step [600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [700/6957] - Training Loss: 0.0086 - Training Accuracy: 99.95% | |
| Step [800/6957] - Training Loss: 0.0000 - Training Accuracy: 99.91% | |
| Step [900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.89% | |
| Step [1000/6957] - Training Loss: 0.0001 - Training Accuracy: 99.87% | |
| Step [1100/6957] - Training Loss: 0.0000 - Training Accuracy: 99.88% | |
| Step [1200/6957] - Training Loss: 0.0000 - Training Accuracy: 99.88% | |
| Step [1300/6957] - Training Loss: 0.0000 - Training Accuracy: 99.89% | |
| Step [1400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.90% | |
| Step [1500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.90% | |
| Step [1600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.90% | |
| Step [1700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.90% | |
| Step [1800/6957] - Training Loss: 0.0000 - Training Accuracy: 99.91% | |
| Step [1900/6957] - Training Loss: 0.0001 - Training Accuracy: 99.91% | |
| Step [2000/6957] - Training Loss: 0.0001 - Training Accuracy: 99.91% | |
| Step [2100/6957] - Training Loss: 0.0000 - Training Accuracy: 99.92% | |
| Step [2200/6957] - Training Loss: 0.0000 - Training Accuracy: 99.92% | |
| Step [2300/6957] - Training Loss: 0.0000 - Training Accuracy: 99.92% | |
| Step [2400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.93% | |
| Step [2500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.93% | |
| Step [2600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.93% | |
| Step [2700/6957] - Training Loss: 0.0001 - Training Accuracy: 99.91% | |
| Step [2800/6957] - Training Loss: 0.0000 - Training Accuracy: 99.91% | |
| Step [2900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.92% | |
| Step [3000/6957] - Training Loss: 0.0000 - Training Accuracy: 99.92% | |
| Step [3100/6957] - Training Loss: 0.0000 - Training Accuracy: 99.92% | |
| Step [3200/6957] - Training Loss: 0.0000 - Training Accuracy: 99.92% | |
| Step [3300/6957] - Training Loss: 0.0000 - Training Accuracy: 99.92% | |
| Step [3400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.92% | |
| Step [3500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.92% | |
| Step [3600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.92% | |
| Step [3700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.92% | |
| Step [3800/6957] - Training Loss: 0.0000 - Training Accuracy: 99.92% | |
| Step [3900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.92% | |
| Step [4000/6957] - Training Loss: 0.0000 - Training Accuracy: 99.92% | |
| Step [4100/6957] - Training Loss: 0.0000 - Training Accuracy: 99.92% | |
| Step [4200/6957] - Training Loss: 0.0002 - Training Accuracy: 99.92% | |
| Step [4300/6957] - Training Loss: 0.0000 - Training Accuracy: 99.92% | |
| Step [4400/6957] - Training Loss: 0.0025 - Training Accuracy: 99.92% | |
| Step [4500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.92% | |
| Step [4600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.92% | |
| Step [4700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.92% | |
| Step [4800/6957] - Training Loss: 0.0000 - Training Accuracy: 99.92% | |
| Step [4900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.92% | |
| Step [5000/6957] - Training Loss: 0.0000 - Training Accuracy: 99.92% | |
| Step [5100/6957] - Training Loss: 0.0000 - Training Accuracy: 99.93% | |
| Step [5200/6957] - Training Loss: 0.0000 - Training Accuracy: 99.93% | |
| Step [5300/6957] - Training Loss: 0.0000 - Training Accuracy: 99.93% | |
| Step [5400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.93% | |
| Step [5500/6957] - Training Loss: 0.0001 - Training Accuracy: 99.93% | |
| Step [5600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.93% | |
| Step [5700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.93% | |
| Step [5800/6957] - Training Loss: 0.0001 - Training Accuracy: 99.93% | |
| Step [5900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.93% | |
| Step [6000/6957] - Training Loss: 0.0000 - Training Accuracy: 99.93% | |
| Step [6100/6957] - Training Loss: 0.0000 - Training Accuracy: 99.93% | |
| Step [6200/6957] - Training Loss: 0.0001 - Training Accuracy: 99.93% | |
| Step [6300/6957] - Training Loss: 0.0018 - Training Accuracy: 99.93% | |
| Step [6400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.93% | |
| Step [6500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.93% | |
| Step [6600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.93% | |
| Step [6700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.93% | |
| Step [6800/6957] - Training Loss: 0.0000 - Training Accuracy: 99.93% | |
| Step [6900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.93% | |
| Epoch [15/20] - Training Loss: 0.0022, Training Accuracy: 99.93% - Validation Loss: 1.3651, Validation Accuracy: 79.68% | |
| Step [100/6957] - Training Loss: 0.0000 - Training Accuracy: 99.94% | |
| Step [200/6957] - Training Loss: 0.0000 - Training Accuracy: 99.88% | |
| Step [300/6957] - Training Loss: 0.0000 - Training Accuracy: 99.92% | |
| Step [400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.94% | |
| Step [500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.95% | |
| Step [600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.94% | |
| Step [700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.94% | |
| Step [800/6957] - Training Loss: 0.0000 - Training Accuracy: 99.93% | |
| Step [900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.93% | |
| Step [1000/6957] - Training Loss: 0.0000 - Training Accuracy: 99.94% | |
| Step [1100/6957] - Training Loss: 0.0000 - Training Accuracy: 99.94% | |
| Step [1200/6957] - Training Loss: 0.0001 - Training Accuracy: 99.94% | |
| Step [1300/6957] - Training Loss: 0.0000 - Training Accuracy: 99.93% | |
| Step [1400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.93% | |
| Step [1500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.93% | |
| Step [1600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.94% | |
| Step [1700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.94% | |
| Step [1800/6957] - Training Loss: 0.0000 - Training Accuracy: 99.94% | |
| Step [1900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.95% | |
| Step [2000/6957] - Training Loss: 0.0000 - Training Accuracy: 99.95% | |
| Step [2100/6957] - Training Loss: 0.0000 - Training Accuracy: 99.95% | |
| Step [2200/6957] - Training Loss: 0.0000 - Training Accuracy: 99.95% | |
| Step [2300/6957] - Training Loss: 0.0000 - Training Accuracy: 99.96% | |
| Step [2400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.96% | |
| Step [2500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.96% | |
| Step [2600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.96% | |
| Step [2700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.96% | |
| Step [2800/6957] - Training Loss: 0.0000 - Training Accuracy: 99.96% | |
| Step [2900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [3000/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [3100/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [3200/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [3300/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [3400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [3500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [3600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [3700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [3800/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [3900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [4000/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [4100/6957] - Training Loss: 0.0001 - Training Accuracy: 99.97% | |
| Step [4200/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [4300/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [4400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [4500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [4600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.96% | |
| Step [4700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.96% | |
| Step [4800/6957] - Training Loss: 0.0000 - Training Accuracy: 99.96% | |
| Step [4900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [5000/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [5100/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [5200/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [5300/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [5400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [5500/6957] - Training Loss: 0.0662 - Training Accuracy: 99.97% | |
| Step [5600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [5700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.96% | |
| Step [5800/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [5900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [6000/6957] - Training Loss: 0.0000 - Training Accuracy: 99.96% | |
| Step [6100/6957] - Training Loss: 0.0000 - Training Accuracy: 99.96% | |
| Step [6200/6957] - Training Loss: 0.0000 - Training Accuracy: 99.96% | |
| Step [6300/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [6400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [6500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [6600/6957] - Training Loss: 0.0001 - Training Accuracy: 99.97% | |
| Step [6700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [6800/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [6900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Epoch [16/20] - Training Loss: 0.0009, Training Accuracy: 99.97% - Validation Loss: 1.7935, Validation Accuracy: 79.28% | |
| Step [100/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [200/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [300/6957] - Training Loss: 0.0000 - Training Accuracy: 99.96% | |
| Step [400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.95% | |
| Step [500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.96% | |
| Step [600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.96% | |
| Step [700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.96% | |
| Step [800/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [1000/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [1100/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [1200/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [1300/6957] - Training Loss: 0.0017 - Training Accuracy: 99.98% | |
| Step [1400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [1500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [1600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [1700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [1800/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [1900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [2000/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [2100/6957] - Training Loss: 0.0000 - Training Accuracy: 99.97% | |
| Step [2200/6957] - Training Loss: 0.0001 - Training Accuracy: 99.97% | |
| Step [2300/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [2400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [2500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [2600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [2700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [2800/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [2900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [3000/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [3100/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [3200/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [3300/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [3400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [3500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [3600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [3700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [3800/6957] - Training Loss: 0.0650 - Training Accuracy: 99.98% | |
| Step [3900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [4000/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [4100/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [4200/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [4300/6957] - Training Loss: 0.0001 - Training Accuracy: 99.98% | |
| Step [4400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [4500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [4600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [4700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [4800/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [4900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [5000/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [5100/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [5200/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [5300/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [5400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [5500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [5600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [5700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [5800/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [5900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [6000/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [6100/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [6200/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [6300/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [6400/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [6500/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [6600/6957] - Training Loss: 0.0000 - Training Accuracy: 99.98% | |
| Step [6700/6957] - Training Loss: 0.0000 - Training Accuracy: 99.99% | |
| Step [6800/6957] - Training Loss: 0.0000 - Training Accuracy: 99.99% | |
| Step [6900/6957] - Training Loss: 0.0000 - Training Accuracy: 99.99% | |
| Epoch [17/20] - Training Loss: 0.0004, Training Accuracy: 99.99% - Validation Loss: 1.9586, Validation Accuracy: 80.55% | |
| Step [100/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [200/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [300/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [400/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [500/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [600/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [700/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [800/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [900/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [1000/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [1100/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [1200/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [1300/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [1400/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [1500/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [1600/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [1700/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [1800/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [1900/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [2000/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [2100/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [2200/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [2300/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [2400/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [2500/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [2600/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [2700/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [2800/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [2900/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [3000/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [3100/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [3200/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [3300/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [3400/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [3500/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [3600/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [3700/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [3800/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [3900/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [4000/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [4100/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [4200/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [4300/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [4400/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [4500/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [4600/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [4700/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [4800/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [4900/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [5000/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [5100/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [5200/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [5300/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [5400/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [5500/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [5600/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [5700/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [5800/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [5900/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [6000/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [6100/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [6200/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [6300/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [6400/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [6500/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [6600/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [6700/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [6800/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [6900/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Epoch [18/20] - Training Loss: 0.0000, Training Accuracy: 100.00% - Validation Loss: 2.1710, Validation Accuracy: 80.06% | |
| Step [100/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [200/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [300/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [400/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [500/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [600/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [700/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [800/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [900/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [1000/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [1100/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [1200/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [1300/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [1400/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [1500/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [1600/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [1700/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [1800/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [1900/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [2000/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [2100/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [2200/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [2300/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [2400/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [2500/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [2600/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [2700/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [2800/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [2900/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [3000/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [3100/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [3200/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [3300/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [3400/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [3500/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [3600/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [3700/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [3800/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [3900/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [4000/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [4100/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [4200/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [4300/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [4400/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [4500/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [4600/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [4700/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [4800/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [4900/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [5000/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [5100/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [5200/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [5300/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [5400/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [5500/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [5600/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [5700/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [5800/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [5900/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [6000/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [6100/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [6200/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [6300/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [6400/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [6500/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [6600/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [6700/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [6800/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [6900/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Epoch [19/20] - Training Loss: 0.0000, Training Accuracy: 100.00% - Validation Loss: 2.3372, Validation Accuracy: 79.99% | |
| Step [100/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [200/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [300/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [400/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [500/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [600/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [700/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [800/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [900/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [1000/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [1100/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [1200/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [1300/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [1400/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [1500/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [1600/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [1700/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [1800/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [1900/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [2000/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [2100/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [2200/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [2300/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [2400/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [2500/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [2600/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [2700/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [2800/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [2900/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [3000/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [3100/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [3200/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [3300/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [3400/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [3500/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [3600/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [3700/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [3800/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [3900/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [4000/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [4100/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [4200/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [4300/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [4400/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [4500/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [4600/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [4700/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [4800/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [4900/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [5000/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [5100/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [5200/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [5300/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [5400/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [5500/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [5600/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [5700/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [5800/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [5900/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [6000/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [6100/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [6200/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [6300/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [6400/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [6500/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [6600/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [6700/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [6800/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Step [6900/6957] - Training Loss: 0.0000 - Training Accuracy: 100.00% | |
| Epoch [20/20] - Training Loss: 0.0000, Training Accuracy: 100.00% - Validation Loss: 2.3948, Validation Accuracy: 80.00% | |
| [1;34mwandb[0m: 🚀 View run [33mHCPflat_large_gsrFalse__beta_sex_HCPFT[0m at: [34mhttps://stability.wandb.io/ckadirt/fMRI-foundation-model/runs/HCPflat_large_gsrFalse__beta_sex_HCPFT_83810[0m | |
| [1;34mwandb[0m: Find logs at: [1;35mwandb/run-20241126_214406-HCPflat_large_gsrFalse__beta_sex_HCPFT_83810/logs[0m | |