| [2026-03-12 11:52:31 LinearSpectre] (3675809339.py 65): INFO LinearSpectre( |
| (patch_embed): V2PatchEmbed( |
| (proj): Sequential( |
| (0): Conv2d(3, 96, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1)) |
| (1): LayerNorm2d((96,), eps=1e-05, elementwise_affine=True) |
| (2): SiLU() |
| (3): Conv2d(96, 192, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1)) |
| (4): LayerNorm2d((192,), eps=1e-05, elementwise_affine=True) |
| (5): SiLU() |
| ) |
| ) |
| (pos_drop): Dropout(p=0.0, inplace=False) |
| (head): Linear(in_features=192, out_features=102, bias=True) |
| (blocks1): ModuleList( |
| (0-5): 6 x SPECTREBlock( |
| (ln1): LayerNorm((192,), eps=1e-05, elementwise_affine=True) |
| (spectre): SPECTRELayer( |
| (q_proj): Linear(in_features=192, out_features=192, bias=False) |
| (v_proj): Linear(in_features=192, out_features=192, bias=False) |
| (out_proj): Linear(in_features=192, out_features=192, bias=False) |
| (gate_mlp): Sequential( |
| (0): LayerNorm((32,), eps=1e-05, elementwise_affine=True) |
| (1): Linear(in_features=32, out_features=128, bias=True) |
| (2): GELU(approximate='none') |
| (3): Linear(in_features=128, out_features=3138, bias=True) |
| ) |
| ) |
| (ln2): LayerNorm((192,), eps=1e-05, elementwise_affine=True) |
| (lnPE): LayerNorm((192,), eps=1e-05, elementwise_affine=True) |
| (ffn): Sequential( |
| (0): Linear(in_features=192, out_features=768, bias=True) |
| (1): GELU(approximate='none') |
| (2): Linear(in_features=768, out_features=192, bias=True) |
| ) |
| ) |
| ) |
| (blocks): ModuleList( |
| (0-5): 6 x GLABlock( |
| (drop_path): DropPath(drop_prob=0.200) |
| (attn_norm): RMSNorm() |
| (lnPE): LayerNorm((192,), eps=1e-05, elementwise_affine=True) |
| (attn): GatedLinearAttention( |
| (gate_fn): SiLU() |
| (out_act): SiLU() |
| (in_proj): Sequential( |
| (0): Conv2d(192, 192, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=192) |
| (1): SiLU() |
| ) |
| (qkv_proj): Linear(in_features=192, out_features=384, bias=False) |
| (gk_proj): Sequential( |
| (0): Linear(in_features=192, out_features=16, bias=False) |
| (1): Linear(in_features=16, out_features=192, bias=True) |
| ) |
| (o_proj): Linear(in_features=192, out_features=192, bias=False) |
| (g_norm): RMSNorm() |
| (l_norm): RMSNorm() |
| (g_proj): Linear(in_features=192, out_features=192, bias=True) |
| (rotary): RotaryEmbeddingFast2D() |
| ) |
| (mlp_norm): RMSNorm() |
| (mlp): GLAMLP( |
| (gate_proj): Linear(in_features=192, out_features=1024, bias=False) |
| (down_proj): Linear(in_features=512, out_features=192, bias=False) |
| (act_fn): SiLU() |
| ) |
| ) |
| ) |
| (norm): RMSNorm() |
| (normPE): LayerNorm((192,), eps=1e-05, elementwise_affine=True) |
| (gap): AdaptiveAvgPool2d(output_size=(1, 1)) |
| ) |
| [2026-03-12 11:52:31 LinearSpectre] (3675809339.py 69): INFO Trainable parameters: 8465310 |
| [2026-03-12 11:52:31 LinearSpectre] (920838639.py 22): INFO No checkpoint found, starting from scratch. |
| [2026-03-12 11:53:50 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [1/300] Train Time: 64.47s | Val Time: 14.81s |
| Train Acc: @1:0.79% @5:4.76% | Loss: 4.5861 |
| Val Acc: @1:0.78% @5:5.10% | Loss: 4.6381 |
| [2026-03-12 11:53:51 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 1, accuracy: 0.78% |
| [2026-03-12 11:54:55 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [2/300] Train Time: 45.62s | Val Time: 13.99s |
| Train Acc: @1:0.99% @5:5.06% | Loss: 4.5759 |
| Val Acc: @1:0.78% @5:5.10% | Loss: 4.6380 |
| [2026-03-12 11:55:55 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [3/300] Train Time: 45.61s | Val Time: 13.97s |
| Train Acc: @1:1.29% @5:6.05% | Loss: 4.5670 |
| Val Acc: @1:0.78% @5:5.10% | Loss: 4.6375 |
| [2026-03-12 11:56:55 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [4/300] Train Time: 45.61s | Val Time: 13.98s |
| Train Acc: @1:1.88% @5:11.11% | Loss: 4.4741 |
| Val Acc: @1:0.78% @5:5.10% | Loss: 4.6366 |
| [2026-03-12 11:57:55 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [5/300] Train Time: 45.62s | Val Time: 14.00s |
| Train Acc: @1:3.08% @5:12.60% | Loss: 4.3770 |
| Val Acc: @1:0.78% @5:5.10% | Loss: 4.6354 |
| [2026-03-12 11:59:00 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [6/300] Train Time: 46.29s | Val Time: 14.01s |
| Train Acc: @1:3.27% @5:16.27% | Loss: 4.2789 |
| Val Acc: @1:0.78% @5:5.39% | Loss: 4.6339 |
| [2026-03-12 12:00:00 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [7/300] Train Time: 45.63s | Val Time: 13.99s |
| Train Acc: @1:3.57% @5:18.75% | Loss: 4.1683 |
| Val Acc: @1:0.78% @5:5.39% | Loss: 4.6321 |
| [2026-03-12 12:01:00 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [8/300] Train Time: 45.62s | Val Time: 14.01s |
| Train Acc: @1:4.76% @5:19.84% | Loss: 4.1621 |
| Val Acc: @1:0.88% @5:5.39% | Loss: 4.6302 |
| [2026-03-12 12:01:01 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 8, accuracy: 0.88% |
| [2026-03-12 12:02:05 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [9/300] Train Time: 45.62s | Val Time: 13.98s |
| Train Acc: @1:4.76% @5:20.44% | Loss: 4.0872 |
| Val Acc: @1:0.98% @5:5.59% | Loss: 4.6280 |
| [2026-03-12 12:02:06 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 9, accuracy: 0.98% |
| [2026-03-12 12:03:10 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [10/300] Train Time: 45.65s | Val Time: 13.97s |
| Train Acc: @1:6.25% @5:23.91% | Loss: 4.0974 |
| Val Acc: @1:0.88% @5:5.69% | Loss: 4.6257 |
| [2026-03-12 12:04:15 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [11/300] Train Time: 45.62s | Val Time: 13.96s |
| Train Acc: @1:5.65% @5:24.01% | Loss: 4.0644 |
| Val Acc: @1:0.78% @5:5.98% | Loss: 4.6231 |
| [2026-03-12 12:05:15 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [12/300] Train Time: 45.59s | Val Time: 13.96s |
| Train Acc: @1:8.43% @5:27.48% | Loss: 4.0026 |
| Val Acc: @1:0.78% @5:6.08% | Loss: 4.6204 |
| [2026-03-12 12:06:15 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [13/300] Train Time: 45.60s | Val Time: 13.96s |
| Train Acc: @1:7.04% @5:27.38% | Loss: 3.9853 |
| Val Acc: @1:0.78% @5:6.18% | Loss: 4.6175 |
| [2026-03-12 12:07:15 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [14/300] Train Time: 45.61s | Val Time: 13.96s |
| Train Acc: @1:8.33% @5:27.78% | Loss: 3.9671 |
| Val Acc: @1:0.88% @5:6.37% | Loss: 4.6144 |
| [2026-03-12 12:08:15 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [15/300] Train Time: 45.61s | Val Time: 13.96s |
| Train Acc: @1:7.24% @5:26.88% | Loss: 3.9743 |
| Val Acc: @1:0.88% @5:6.47% | Loss: 4.6111 |
| [2026-03-12 12:09:20 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [16/300] Train Time: 45.67s | Val Time: 13.99s |
| Train Acc: @1:8.53% @5:28.17% | Loss: 3.9769 |
| Val Acc: @1:0.78% @5:6.96% | Loss: 4.6077 |
| [2026-03-12 12:10:20 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [17/300] Train Time: 45.61s | Val Time: 13.96s |
| Train Acc: @1:9.23% @5:29.66% | Loss: 3.9161 |
| Val Acc: @1:0.88% @5:7.35% | Loss: 4.6041 |
| [2026-03-12 12:11:20 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [18/300] Train Time: 45.63s | Val Time: 13.96s |
| Train Acc: @1:10.71% @5:30.75% | Loss: 3.8936 |
| Val Acc: @1:0.88% @5:7.75% | Loss: 4.6003 |
| [2026-03-12 12:12:20 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [19/300] Train Time: 45.62s | Val Time: 13.98s |
| Train Acc: @1:9.62% @5:31.15% | Loss: 3.8999 |
| Val Acc: @1:1.08% @5:7.75% | Loss: 4.5963 |
| [2026-03-12 12:12:20 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 19, accuracy: 1.08% |
| [2026-03-12 12:13:25 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [20/300] Train Time: 45.64s | Val Time: 13.97s |
| Train Acc: @1:7.34% @5:29.46% | Loss: 3.9271 |
| Val Acc: @1:1.27% @5:8.24% | Loss: 4.5921 |
| [2026-03-12 12:13:31 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 20, accuracy: 1.27% |
| [2026-03-12 12:14:37 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [21/300] Train Time: 45.60s | Val Time: 13.96s |
| Train Acc: @1:9.52% @5:32.84% | Loss: 3.8686 |
| Val Acc: @1:1.37% @5:8.24% | Loss: 4.5878 |
| [2026-03-12 12:14:37 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 21, accuracy: 1.37% |
| [2026-03-12 12:15:42 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [22/300] Train Time: 45.63s | Val Time: 13.97s |
| Train Acc: @1:9.42% @5:32.34% | Loss: 3.8713 |
| Val Acc: @1:1.67% @5:8.63% | Loss: 4.5833 |
| [2026-03-12 12:15:43 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 22, accuracy: 1.67% |
| [2026-03-12 12:16:47 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [23/300] Train Time: 45.58s | Val Time: 14.00s |
| Train Acc: @1:10.22% @5:32.44% | Loss: 3.8816 |
| Val Acc: @1:1.76% @5:9.02% | Loss: 4.5786 |
| [2026-03-12 12:16:48 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 23, accuracy: 1.76% |
| [2026-03-12 12:17:53 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [24/300] Train Time: 45.62s | Val Time: 13.98s |
| Train Acc: @1:9.42% @5:34.72% | Loss: 3.8300 |
| Val Acc: @1:1.86% @5:9.12% | Loss: 4.5737 |
| [2026-03-12 12:17:54 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 24, accuracy: 1.86% |
| [2026-03-12 12:19:01 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [25/300] Train Time: 45.60s | Val Time: 13.96s |
| Train Acc: @1:8.53% @5:32.84% | Loss: 3.8700 |
| Val Acc: @1:1.86% @5:9.41% | Loss: 4.5687 |
| [2026-03-12 12:20:09 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [26/300] Train Time: 45.63s | Val Time: 13.97s |
| Train Acc: @1:10.12% @5:34.33% | Loss: 3.8369 |
| Val Acc: @1:2.16% @5:10.00% | Loss: 4.5636 |
| [2026-03-12 12:20:10 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 26, accuracy: 2.16% |
| [2026-03-12 12:21:15 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [27/300] Train Time: 45.63s | Val Time: 13.99s |
| Train Acc: @1:8.63% @5:34.52% | Loss: 3.8151 |
| Val Acc: @1:2.06% @5:10.69% | Loss: 4.5583 |
| [2026-03-12 12:22:15 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [28/300] Train Time: 45.66s | Val Time: 14.03s |
| Train Acc: @1:10.71% @5:34.72% | Loss: 3.7958 |
| Val Acc: @1:2.55% @5:11.47% | Loss: 4.5529 |
| [2026-03-12 12:22:16 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 28, accuracy: 2.55% |
| [2026-03-12 12:23:23 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [29/300] Train Time: 45.69s | Val Time: 13.99s |
| Train Acc: @1:8.93% @5:34.62% | Loss: 3.8058 |
| Val Acc: @1:2.84% @5:11.47% | Loss: 4.5473 |
| [2026-03-12 12:23:24 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 29, accuracy: 2.84% |
| [2026-03-12 12:24:31 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [30/300] Train Time: 45.62s | Val Time: 13.97s |
| Train Acc: @1:13.19% @5:36.81% | Loss: 3.7711 |
| Val Acc: @1:3.04% @5:12.06% | Loss: 4.5416 |
| [2026-03-12 12:24:39 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 30, accuracy: 3.04% |
| [2026-03-12 12:25:46 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [31/300] Train Time: 45.64s | Val Time: 13.98s |
| Train Acc: @1:13.19% @5:36.01% | Loss: 3.7343 |
| Val Acc: @1:3.14% @5:12.06% | Loss: 4.5358 |
| [2026-03-12 12:25:46 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 31, accuracy: 3.14% |
| [2026-03-12 12:26:54 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [32/300] Train Time: 45.68s | Val Time: 14.00s |
| Train Acc: @1:11.31% @5:38.69% | Loss: 3.7195 |
| Val Acc: @1:3.43% @5:12.25% | Loss: 4.5298 |
| [2026-03-12 12:26:54 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 32, accuracy: 3.43% |
| [2026-03-12 12:28:19 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [33/300] Train Time: 45.65s | Val Time: 13.98s |
| Train Acc: @1:14.68% @5:38.59% | Loss: 3.7083 |
| Val Acc: @1:3.53% @5:12.45% | Loss: 4.5236 |
| [2026-03-12 12:28:19 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 33, accuracy: 3.53% |
| [2026-03-12 12:29:25 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [34/300] Train Time: 46.31s | Val Time: 14.04s |
| Train Acc: @1:12.50% @5:38.79% | Loss: 3.6879 |
| Val Acc: @1:3.53% @5:12.94% | Loss: 4.5173 |
| [2026-03-12 12:30:25 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [35/300] Train Time: 45.68s | Val Time: 14.00s |
| Train Acc: @1:14.19% @5:40.38% | Loss: 3.6625 |
| Val Acc: @1:3.63% @5:12.84% | Loss: 4.5108 |
| [2026-03-12 12:30:31 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 35, accuracy: 3.63% |
| [2026-03-12 12:31:37 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [36/300] Train Time: 45.70s | Val Time: 14.04s |
| Train Acc: @1:15.28% @5:41.67% | Loss: 3.6367 |
| Val Acc: @1:3.73% @5:13.04% | Loss: 4.5041 |
| [2026-03-12 12:31:38 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 36, accuracy: 3.73% |
| [2026-03-12 12:32:43 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [37/300] Train Time: 45.68s | Val Time: 14.04s |
| Train Acc: @1:14.38% @5:41.96% | Loss: 3.6506 |
| Val Acc: @1:3.82% @5:13.04% | Loss: 4.4973 |
| [2026-03-12 12:32:44 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 37, accuracy: 3.82% |
| [2026-03-12 12:33:50 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [38/300] Train Time: 45.75s | Val Time: 14.09s |
| Train Acc: @1:14.78% @5:41.96% | Loss: 3.6291 |
| Val Acc: @1:3.73% @5:13.43% | Loss: 4.4903 |
| [2026-03-12 12:34:50 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [39/300] Train Time: 45.73s | Val Time: 14.05s |
| Train Acc: @1:16.67% @5:43.35% | Loss: 3.6176 |
| Val Acc: @1:3.82% @5:13.33% | Loss: 4.4831 |
| [2026-03-12 12:35:50 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [40/300] Train Time: 45.70s | Val Time: 14.04s |
| Train Acc: @1:15.08% @5:44.64% | Loss: 3.5997 |
| Val Acc: @1:4.02% @5:13.73% | Loss: 4.4758 |
| [2026-03-12 12:35:59 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 40, accuracy: 4.02% |
| [2026-03-12 12:37:06 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [41/300] Train Time: 45.70s | Val Time: 14.04s |
| Train Acc: @1:15.38% @5:44.35% | Loss: 3.6050 |
| Val Acc: @1:4.02% @5:14.02% | Loss: 4.4683 |
| [2026-03-12 12:38:07 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [42/300] Train Time: 45.69s | Val Time: 14.03s |
| Train Acc: @1:17.36% @5:46.23% | Loss: 3.5578 |
| Val Acc: @1:4.12% @5:14.22% | Loss: 4.4607 |
| [2026-03-12 12:38:07 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 42, accuracy: 4.12% |
| [2026-03-12 12:39:15 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [43/300] Train Time: 45.77s | Val Time: 14.04s |
| Train Acc: @1:17.36% @5:44.54% | Loss: 3.5309 |
| Val Acc: @1:4.51% @5:14.61% | Loss: 4.4530 |
| [2026-03-12 12:39:15 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 43, accuracy: 4.51% |
| [2026-03-12 12:40:22 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [44/300] Train Time: 45.68s | Val Time: 14.05s |
| Train Acc: @1:17.56% @5:46.83% | Loss: 3.5127 |
| Val Acc: @1:4.51% @5:14.80% | Loss: 4.4452 |
| [2026-03-12 12:41:23 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [45/300] Train Time: 45.74s | Val Time: 14.07s |
| Train Acc: @1:19.84% @5:49.01% | Loss: 3.4454 |
| Val Acc: @1:5.20% @5:14.90% | Loss: 4.4372 |
| [2026-03-12 12:41:30 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 45, accuracy: 5.20% |
| [2026-03-12 12:42:38 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [46/300] Train Time: 45.70s | Val Time: 14.07s |
| Train Acc: @1:18.85% @5:48.61% | Loss: 3.4607 |
| Val Acc: @1:5.29% @5:15.10% | Loss: 4.4291 |
| [2026-03-12 12:42:38 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 46, accuracy: 5.29% |
| [2026-03-12 12:43:44 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [47/300] Train Time: 45.74s | Val Time: 14.06s |
| Train Acc: @1:17.16% @5:48.31% | Loss: 3.4945 |
| Val Acc: @1:5.29% @5:15.39% | Loss: 4.4210 |
| [2026-03-12 12:44:44 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [48/300] Train Time: 45.73s | Val Time: 14.03s |
| Train Acc: @1:19.15% @5:49.31% | Loss: 3.4517 |
| Val Acc: @1:5.49% @5:15.88% | Loss: 4.4129 |
| [2026-03-12 12:44:45 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 48, accuracy: 5.49% |
| [2026-03-12 12:45:53 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [49/300] Train Time: 45.75s | Val Time: 14.06s |
| Train Acc: @1:19.25% @5:48.41% | Loss: 3.4525 |
| Val Acc: @1:5.78% @5:16.18% | Loss: 4.4048 |
| [2026-03-12 12:45:54 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 49, accuracy: 5.78% |
| [2026-03-12 12:47:01 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [50/300] Train Time: 45.75s | Val Time: 14.08s |
| Train Acc: @1:18.95% @5:48.71% | Loss: 3.4082 |
| Val Acc: @1:5.39% @5:16.57% | Loss: 4.3966 |
| [2026-03-12 12:48:08 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [51/300] Train Time: 45.70s | Val Time: 14.05s |
| Train Acc: @1:21.13% @5:52.18% | Loss: 3.4037 |
| Val Acc: @1:5.59% @5:17.35% | Loss: 4.3887 |
| [2026-03-12 12:49:08 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [52/300] Train Time: 45.71s | Val Time: 14.06s |
| Train Acc: @1:21.73% @5:53.67% | Loss: 3.3491 |
| Val Acc: @1:5.20% @5:17.25% | Loss: 4.3808 |
| [2026-03-12 12:50:08 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [53/300] Train Time: 45.74s | Val Time: 14.06s |
| Train Acc: @1:21.73% @5:51.98% | Loss: 3.4014 |
| Val Acc: @1:5.00% @5:17.84% | Loss: 4.3731 |
| [2026-03-12 12:51:08 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [54/300] Train Time: 45.70s | Val Time: 14.07s |
| Train Acc: @1:21.53% @5:51.79% | Loss: 3.3575 |
| Val Acc: @1:5.00% @5:17.84% | Loss: 4.3655 |
| [2026-03-12 12:52:08 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [55/300] Train Time: 45.65s | Val Time: 14.10s |
| Train Acc: @1:23.41% @5:55.46% | Loss: 3.3020 |
| Val Acc: @1:5.10% @5:18.92% | Loss: 4.3582 |
| [2026-03-12 12:53:15 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [56/300] Train Time: 45.77s | Val Time: 14.08s |
| Train Acc: @1:25.10% @5:56.85% | Loss: 3.2525 |
| Val Acc: @1:5.29% @5:18.53% | Loss: 4.3510 |
| [2026-03-12 12:54:15 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [57/300] Train Time: 45.72s | Val Time: 14.05s |
| Train Acc: @1:23.51% @5:55.65% | Loss: 3.2645 |
| Val Acc: @1:5.49% @5:18.63% | Loss: 4.3438 |
| [2026-03-12 12:55:15 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [58/300] Train Time: 45.76s | Val Time: 14.07s |
| Train Acc: @1:24.80% @5:55.06% | Loss: 3.3090 |
| Val Acc: @1:5.59% @5:19.51% | Loss: 4.3366 |
| [2026-03-12 12:56:15 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [59/300] Train Time: 45.77s | Val Time: 14.12s |
| Train Acc: @1:24.60% @5:56.55% | Loss: 3.2761 |
| Val Acc: @1:5.78% @5:20.39% | Loss: 4.3297 |
| [2026-03-12 12:57:16 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [60/300] Train Time: 45.81s | Val Time: 14.14s |
| Train Acc: @1:24.90% @5:57.04% | Loss: 3.2160 |
| Val Acc: @1:5.69% @5:20.20% | Loss: 4.3229 |
| [2026-03-12 12:58:22 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [61/300] Train Time: 46.51s | Val Time: 14.17s |
| Train Acc: @1:27.18% @5:59.82% | Loss: 3.1885 |
| Val Acc: @1:5.88% @5:21.27% | Loss: 4.3163 |
| [2026-03-12 12:58:23 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 61, accuracy: 5.88% |
| [2026-03-12 12:59:29 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [62/300] Train Time: 45.86s | Val Time: 14.13s |
| Train Acc: @1:26.19% @5:56.45% | Loss: 3.2206 |
| Val Acc: @1:5.78% @5:21.57% | Loss: 4.3098 |
| [2026-03-12 13:00:29 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [63/300] Train Time: 45.76s | Val Time: 14.13s |
| Train Acc: @1:25.99% @5:59.52% | Loss: 3.1697 |
| Val Acc: @1:5.88% @5:21.76% | Loss: 4.3032 |
| [2026-03-12 13:01:29 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [64/300] Train Time: 45.80s | Val Time: 14.14s |
| Train Acc: @1:28.08% @5:60.12% | Loss: 3.1472 |
| Val Acc: @1:5.88% @5:21.86% | Loss: 4.2964 |
| [2026-03-12 13:02:30 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [65/300] Train Time: 45.89s | Val Time: 14.11s |
| Train Acc: @1:27.58% @5:60.22% | Loss: 3.1416 |
| Val Acc: @1:5.88% @5:22.25% | Loss: 4.2895 |
| [2026-03-12 13:03:35 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [66/300] Train Time: 45.77s | Val Time: 14.10s |
| Train Acc: @1:28.67% @5:60.62% | Loss: 3.1063 |
| Val Acc: @1:5.98% @5:22.55% | Loss: 4.2829 |
| [2026-03-12 13:03:35 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 66, accuracy: 5.98% |
| [2026-03-12 13:04:49 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [67/300] Train Time: 45.85s | Val Time: 14.11s |
| Train Acc: @1:30.85% @5:63.69% | Loss: 3.0704 |
| Val Acc: @1:5.88% @5:22.75% | Loss: 4.2760 |
| [2026-03-12 13:05:49 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [68/300] Train Time: 45.82s | Val Time: 14.12s |
| Train Acc: @1:27.38% @5:61.11% | Loss: 3.1045 |
| Val Acc: @1:5.69% @5:23.04% | Loss: 4.2688 |
| [2026-03-12 13:06:49 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [69/300] Train Time: 45.77s | Val Time: 14.13s |
| Train Acc: @1:29.66% @5:62.70% | Loss: 3.0683 |
| Val Acc: @1:5.78% @5:23.43% | Loss: 4.2619 |
| [2026-03-12 13:07:49 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [70/300] Train Time: 45.81s | Val Time: 14.12s |
| Train Acc: @1:28.67% @5:62.40% | Loss: 3.0630 |
| Val Acc: @1:5.88% @5:24.41% | Loss: 4.2548 |
| [2026-03-12 13:08:55 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [71/300] Train Time: 45.80s | Val Time: 14.12s |
| Train Acc: @1:32.04% @5:63.19% | Loss: 2.9752 |
| Val Acc: @1:5.88% @5:25.59% | Loss: 4.2481 |
| [2026-03-12 13:09:55 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [72/300] Train Time: 45.71s | Val Time: 14.10s |
| Train Acc: @1:30.65% @5:62.40% | Loss: 3.0570 |
| Val Acc: @1:6.18% @5:26.08% | Loss: 4.2408 |
| [2026-03-12 13:09:56 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 72, accuracy: 6.18% |
| [2026-03-12 13:11:02 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [73/300] Train Time: 45.85s | Val Time: 14.14s |
| Train Acc: @1:32.14% @5:63.69% | Loss: 3.0120 |
| Val Acc: @1:6.47% @5:26.76% | Loss: 4.2340 |
| [2026-03-12 13:11:03 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 73, accuracy: 6.47% |
| [2026-03-12 13:12:12 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [74/300] Train Time: 45.86s | Val Time: 14.15s |
| Train Acc: @1:33.93% @5:69.44% | Loss: 2.8948 |
| Val Acc: @1:6.67% @5:26.67% | Loss: 4.2276 |
| [2026-03-12 13:12:13 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 74, accuracy: 6.67% |
| [2026-03-12 13:13:19 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [75/300] Train Time: 45.85s | Val Time: 14.13s |
| Train Acc: @1:31.94% @5:65.77% | Loss: 2.9783 |
| Val Acc: @1:7.06% @5:26.76% | Loss: 4.2214 |
| [2026-03-12 13:13:25 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 75, accuracy: 7.06% |
| [2026-03-12 13:14:31 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [76/300] Train Time: 45.85s | Val Time: 14.14s |
| Train Acc: @1:32.64% @5:65.67% | Loss: 2.9740 |
| Val Acc: @1:7.65% @5:27.06% | Loss: 4.2153 |
| [2026-03-12 13:14:32 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 76, accuracy: 7.65% |
| [2026-03-12 13:15:37 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [77/300] Train Time: 45.88s | Val Time: 14.11s |
| Train Acc: @1:33.53% @5:65.08% | Loss: 2.9479 |
| Val Acc: @1:7.84% @5:27.65% | Loss: 4.2093 |
| [2026-03-12 13:15:38 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 77, accuracy: 7.84% |
| [2026-03-12 13:16:54 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [78/300] Train Time: 45.92s | Val Time: 14.13s |
| Train Acc: @1:35.81% @5:66.17% | Loss: 2.9447 |
| Val Acc: @1:8.53% @5:28.43% | Loss: 4.2036 |
| [2026-03-12 13:16:55 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 78, accuracy: 8.53% |
| [2026-03-12 13:17:59 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [79/300] Train Time: 45.82s | Val Time: 14.13s |
| Train Acc: @1:37.30% @5:70.73% | Loss: 2.8305 |
| Val Acc: @1:8.63% @5:28.82% | Loss: 4.1983 |
| [2026-03-12 13:18:00 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 79, accuracy: 8.63% |
| [2026-03-12 13:19:05 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [80/300] Train Time: 45.91s | Val Time: 14.13s |
| Train Acc: @1:36.71% @5:72.32% | Loss: 2.7891 |
| Val Acc: @1:8.63% @5:29.80% | Loss: 4.1928 |
| [2026-03-12 13:20:10 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [81/300] Train Time: 45.85s | Val Time: 14.12s |
| Train Acc: @1:37.90% @5:70.93% | Loss: 2.8352 |
| Val Acc: @1:8.73% @5:30.39% | Loss: 4.1874 |
| [2026-03-12 13:20:11 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 81, accuracy: 8.73% |
| [2026-03-12 13:21:16 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [82/300] Train Time: 45.86s | Val Time: 14.12s |
| Train Acc: @1:39.68% @5:69.54% | Loss: 2.8060 |
| Val Acc: @1:8.82% @5:30.49% | Loss: 4.1821 |
| [2026-03-12 13:21:16 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 82, accuracy: 8.82% |
| [2026-03-12 13:22:21 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [83/300] Train Time: 45.89s | Val Time: 14.13s |
| Train Acc: @1:37.40% @5:70.93% | Loss: 2.7823 |
| Val Acc: @1:9.31% @5:30.49% | Loss: 4.1770 |
| [2026-03-12 13:22:22 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 83, accuracy: 9.31% |
| [2026-03-12 13:23:27 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [84/300] Train Time: 45.86s | Val Time: 14.13s |
| Train Acc: @1:41.27% @5:71.23% | Loss: 2.7614 |
| Val Acc: @1:9.61% @5:30.69% | Loss: 4.1720 |
| [2026-03-12 13:23:27 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 84, accuracy: 9.61% |
| [2026-03-12 13:24:38 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [85/300] Train Time: 45.90s | Val Time: 14.17s |
| Train Acc: @1:41.37% @5:72.52% | Loss: 2.7241 |
| Val Acc: @1:9.90% @5:30.78% | Loss: 4.1668 |
| [2026-03-12 13:24:43 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 85, accuracy: 9.90% |
| [2026-03-12 13:25:50 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [86/300] Train Time: 45.89s | Val Time: 14.24s |
| Train Acc: @1:41.87% @5:74.80% | Loss: 2.6958 |
| Val Acc: @1:9.71% @5:31.08% | Loss: 4.1618 |
| [2026-03-12 13:26:50 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [87/300] Train Time: 45.81s | Val Time: 14.14s |
| Train Acc: @1:40.87% @5:72.02% | Loss: 2.7214 |
| Val Acc: @1:10.10% @5:31.27% | Loss: 4.1569 |
| [2026-03-12 13:26:51 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 87, accuracy: 10.10% |
| [2026-03-12 13:27:57 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [88/300] Train Time: 46.62s | Val Time: 14.28s |
| Train Acc: @1:41.67% @5:73.51% | Loss: 2.7003 |
| Val Acc: @1:10.39% @5:31.37% | Loss: 4.1521 |
| [2026-03-12 13:27:57 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 88, accuracy: 10.39% |
| [2026-03-12 13:29:02 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [89/300] Train Time: 45.88s | Val Time: 14.14s |
| Train Acc: @1:42.86% @5:75.00% | Loss: 2.6451 |
| Val Acc: @1:10.39% @5:32.16% | Loss: 4.1473 |
| [2026-03-12 13:30:02 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [90/300] Train Time: 45.90s | Val Time: 14.17s |
| Train Acc: @1:41.96% @5:74.40% | Loss: 2.6798 |
| Val Acc: @1:10.39% @5:32.65% | Loss: 4.1427 |
| [2026-03-12 13:31:07 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [91/300] Train Time: 45.85s | Val Time: 14.16s |
| Train Acc: @1:45.54% @5:75.20% | Loss: 2.6042 |
| Val Acc: @1:10.49% @5:32.65% | Loss: 4.1386 |
| [2026-03-12 13:31:08 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 91, accuracy: 10.49% |
| [2026-03-12 13:32:13 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [92/300] Train Time: 45.90s | Val Time: 14.15s |
| Train Acc: @1:45.24% @5:76.29% | Loss: 2.5638 |
| Val Acc: @1:10.88% @5:32.65% | Loss: 4.1342 |
| [2026-03-12 13:32:14 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 92, accuracy: 10.88% |
| [2026-03-12 13:33:19 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [93/300] Train Time: 45.82s | Val Time: 14.17s |
| Train Acc: @1:49.01% @5:76.79% | Loss: 2.5413 |
| Val Acc: @1:11.08% @5:33.14% | Loss: 4.1299 |
| [2026-03-12 13:33:19 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 93, accuracy: 11.08% |
| [2026-03-12 13:34:24 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [94/300] Train Time: 45.95s | Val Time: 14.15s |
| Train Acc: @1:46.63% @5:77.88% | Loss: 2.5394 |
| Val Acc: @1:10.78% @5:33.14% | Loss: 4.1252 |
| [2026-03-12 13:35:24 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [95/300] Train Time: 45.78s | Val Time: 14.12s |
| Train Acc: @1:45.93% @5:76.88% | Loss: 2.5649 |
| Val Acc: @1:10.78% @5:33.63% | Loss: 4.1205 |
| [2026-03-12 13:36:34 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [96/300] Train Time: 45.86s | Val Time: 14.15s |
| Train Acc: @1:46.23% @5:77.08% | Loss: 2.5649 |
| Val Acc: @1:10.78% @5:33.92% | Loss: 4.1158 |
| [2026-03-12 13:37:34 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [97/300] Train Time: 45.85s | Val Time: 14.13s |
| Train Acc: @1:46.43% @5:77.58% | Loss: 2.5489 |
| Val Acc: @1:10.98% @5:33.73% | Loss: 4.1111 |
| [2026-03-12 13:38:35 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [98/300] Train Time: 45.86s | Val Time: 14.13s |
| Train Acc: @1:49.50% @5:79.37% | Loss: 2.4437 |
| Val Acc: @1:10.98% @5:33.92% | Loss: 4.1067 |
| [2026-03-12 13:39:35 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [99/300] Train Time: 45.83s | Val Time: 14.14s |
| Train Acc: @1:49.50% @5:77.78% | Loss: 2.5026 |
| Val Acc: @1:10.98% @5:33.92% | Loss: 4.1024 |
| [2026-03-12 13:40:36 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [100/300] Train Time: 45.89s | Val Time: 14.26s |
| Train Acc: @1:47.92% @5:78.97% | Loss: 2.5074 |
| Val Acc: @1:10.98% @5:33.92% | Loss: 4.0979 |
| [2026-03-12 13:41:41 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [101/300] Train Time: 45.83s | Val Time: 14.15s |
| Train Acc: @1:51.39% @5:80.75% | Loss: 2.4028 |
| Val Acc: @1:10.98% @5:33.92% | Loss: 4.0934 |
| [2026-03-12 13:42:41 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [102/300] Train Time: 45.82s | Val Time: 14.14s |
| Train Acc: @1:53.67% @5:81.75% | Loss: 2.3837 |
| Val Acc: @1:10.78% @5:34.41% | Loss: 4.0892 |
| [2026-03-12 13:43:41 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [103/300] Train Time: 45.76s | Val Time: 14.10s |
| Train Acc: @1:52.18% @5:79.17% | Loss: 2.3987 |
| Val Acc: @1:10.69% @5:34.41% | Loss: 4.0847 |
| [2026-03-12 13:44:42 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [104/300] Train Time: 45.87s | Val Time: 14.12s |
| Train Acc: @1:54.37% @5:81.55% | Loss: 2.3389 |
| Val Acc: @1:10.69% @5:34.41% | Loss: 4.0801 |
| [2026-03-12 13:45:42 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [105/300] Train Time: 45.85s | Val Time: 14.15s |
| Train Acc: @1:53.97% @5:80.85% | Loss: 2.3537 |
| Val Acc: @1:10.69% @5:34.71% | Loss: 4.0757 |
| [2026-03-12 13:46:47 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [106/300] Train Time: 45.90s | Val Time: 14.17s |
| Train Acc: @1:55.06% @5:80.56% | Loss: 2.3404 |
| Val Acc: @1:10.98% @5:35.20% | Loss: 4.0716 |
| [2026-03-12 13:47:47 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [107/300] Train Time: 45.84s | Val Time: 14.17s |
| Train Acc: @1:55.75% @5:82.74% | Loss: 2.3031 |
| Val Acc: @1:11.18% @5:35.39% | Loss: 4.0675 |
| [2026-03-12 13:47:48 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 107, accuracy: 11.18% |
| [2026-03-12 13:48:53 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [108/300] Train Time: 45.90s | Val Time: 14.16s |
| Train Acc: @1:56.05% @5:82.74% | Loss: 2.2976 |
| Val Acc: @1:11.27% @5:35.49% | Loss: 4.0634 |
| [2026-03-12 13:48:54 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 108, accuracy: 11.27% |
| [2026-03-12 13:49:59 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [109/300] Train Time: 45.91s | Val Time: 14.17s |
| Train Acc: @1:55.46% @5:82.04% | Loss: 2.3080 |
| Val Acc: @1:11.37% @5:35.10% | Loss: 4.0595 |
| [2026-03-12 13:50:00 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 109, accuracy: 11.37% |
| [2026-03-12 13:51:05 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [110/300] Train Time: 45.86s | Val Time: 14.14s |
| Train Acc: @1:57.14% @5:82.84% | Loss: 2.2510 |
| Val Acc: @1:11.27% @5:35.59% | Loss: 4.0554 |
| [2026-03-12 13:52:11 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [111/300] Train Time: 45.86s | Val Time: 14.15s |
| Train Acc: @1:56.85% @5:83.83% | Loss: 2.2526 |
| Val Acc: @1:11.37% @5:35.59% | Loss: 4.0512 |
| [2026-03-12 13:53:11 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [112/300] Train Time: 45.86s | Val Time: 14.17s |
| Train Acc: @1:59.82% @5:84.92% | Loss: 2.1950 |
| Val Acc: @1:11.27% @5:35.69% | Loss: 4.0468 |
| [2026-03-12 13:54:11 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [113/300] Train Time: 45.79s | Val Time: 14.10s |
| Train Acc: @1:57.64% @5:85.52% | Loss: 2.2154 |
| Val Acc: @1:11.27% @5:35.39% | Loss: 4.0426 |
| [2026-03-12 13:55:12 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [114/300] Train Time: 45.74s | Val Time: 14.06s |
| Train Acc: @1:61.01% @5:85.42% | Loss: 2.1413 |
| Val Acc: @1:11.27% @5:35.29% | Loss: 4.0387 |
| [2026-03-12 13:56:12 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [115/300] Train Time: 45.75s | Val Time: 14.08s |
| Train Acc: @1:58.23% @5:84.23% | Loss: 2.1951 |
| Val Acc: @1:11.27% @5:35.29% | Loss: 4.0350 |
| [2026-03-12 13:57:17 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [116/300] Train Time: 45.69s | Val Time: 14.02s |
| Train Acc: @1:62.20% @5:85.62% | Loss: 2.1253 |
| Val Acc: @1:11.47% @5:35.49% | Loss: 4.0312 |
| [2026-03-12 13:57:18 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 116, accuracy: 11.47% |
| [2026-03-12 13:58:23 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [117/300] Train Time: 45.85s | Val Time: 14.06s |
| Train Acc: @1:59.72% @5:87.00% | Loss: 2.1400 |
| Val Acc: @1:11.67% @5:35.59% | Loss: 4.0275 |
| [2026-03-12 13:58:23 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 117, accuracy: 11.67% |
| [2026-03-12 13:59:28 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [118/300] Train Time: 45.77s | Val Time: 14.05s |
| Train Acc: @1:61.61% @5:86.41% | Loss: 2.0972 |
| Val Acc: @1:11.67% @5:35.59% | Loss: 4.0238 |
| [2026-03-12 14:00:28 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [119/300] Train Time: 45.74s | Val Time: 14.05s |
| Train Acc: @1:61.11% @5:86.01% | Loss: 2.1164 |
| Val Acc: @1:11.86% @5:35.49% | Loss: 4.0203 |
| [2026-03-12 14:00:29 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 119, accuracy: 11.86% |
| [2026-03-12 14:01:47 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [120/300] Train Time: 45.86s | Val Time: 14.08s |
| Train Acc: @1:61.01% @5:86.21% | Loss: 2.1154 |
| Val Acc: @1:11.76% @5:35.59% | Loss: 4.0162 |
| [2026-03-12 14:02:52 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [121/300] Train Time: 45.76s | Val Time: 14.02s |
| Train Acc: @1:62.00% @5:86.41% | Loss: 2.1052 |
| Val Acc: @1:11.76% @5:35.59% | Loss: 4.0122 |
| [2026-03-12 14:03:52 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [122/300] Train Time: 45.74s | Val Time: 14.06s |
| Train Acc: @1:63.89% @5:85.71% | Loss: 2.0848 |
| Val Acc: @1:11.86% @5:35.78% | Loss: 4.0082 |
| [2026-03-12 14:04:52 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [123/300] Train Time: 45.65s | Val Time: 14.04s |
| Train Acc: @1:65.67% @5:88.29% | Loss: 2.0038 |
| Val Acc: @1:11.96% @5:35.59% | Loss: 4.0038 |
| [2026-03-12 14:04:53 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 123, accuracy: 11.96% |
| [2026-03-12 14:06:00 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [124/300] Train Time: 45.75s | Val Time: 14.11s |
| Train Acc: @1:64.98% @5:88.59% | Loss: 2.0068 |
| Val Acc: @1:12.25% @5:35.59% | Loss: 3.9996 |
| [2026-03-12 14:06:00 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 124, accuracy: 12.25% |
| [2026-03-12 14:07:06 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [125/300] Train Time: 45.80s | Val Time: 14.05s |
| Train Acc: @1:67.96% @5:87.70% | Loss: 1.9725 |
| Val Acc: @1:12.25% @5:35.78% | Loss: 3.9952 |
| [2026-03-12 14:08:12 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [126/300] Train Time: 45.85s | Val Time: 14.06s |
| Train Acc: @1:64.68% @5:87.00% | Loss: 2.0245 |
| Val Acc: @1:12.45% @5:35.59% | Loss: 3.9912 |
| [2026-03-12 14:08:13 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 126, accuracy: 12.45% |
| [2026-03-12 14:09:19 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [127/300] Train Time: 45.75s | Val Time: 14.08s |
| Train Acc: @1:64.09% @5:86.90% | Loss: 2.0623 |
| Val Acc: @1:12.55% @5:35.78% | Loss: 3.9872 |
| [2026-03-12 14:09:20 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 127, accuracy: 12.55% |
| [2026-03-12 14:10:26 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [128/300] Train Time: 45.83s | Val Time: 14.15s |
| Train Acc: @1:70.04% @5:89.98% | Loss: 1.8758 |
| Val Acc: @1:12.75% @5:35.69% | Loss: 3.9833 |
| [2026-03-12 14:10:26 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 128, accuracy: 12.75% |
| [2026-03-12 14:11:32 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [129/300] Train Time: 45.86s | Val Time: 14.13s |
| Train Acc: @1:68.35% @5:88.59% | Loss: 1.9792 |
| Val Acc: @1:12.75% @5:35.69% | Loss: 3.9796 |
| [2026-03-12 14:12:32 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [130/300] Train Time: 45.89s | Val Time: 14.14s |
| Train Acc: @1:66.57% @5:88.59% | Loss: 1.9816 |
| Val Acc: @1:12.55% @5:35.78% | Loss: 3.9757 |
| [2026-03-12 14:13:38 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [131/300] Train Time: 45.86s | Val Time: 14.19s |
| Train Acc: @1:67.26% @5:89.98% | Loss: 1.9741 |
| Val Acc: @1:12.55% @5:36.18% | Loss: 3.9718 |
| [2026-03-12 14:14:39 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [132/300] Train Time: 45.91s | Val Time: 14.14s |
| Train Acc: @1:69.35% @5:87.90% | Loss: 1.9044 |
| Val Acc: @1:12.94% @5:36.27% | Loss: 3.9679 |
| [2026-03-12 14:14:39 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 132, accuracy: 12.94% |
| [2026-03-12 14:15:45 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [133/300] Train Time: 45.86s | Val Time: 14.14s |
| Train Acc: @1:70.14% @5:90.67% | Loss: 1.8615 |
| Val Acc: @1:13.14% @5:36.47% | Loss: 3.9641 |
| [2026-03-12 14:15:46 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 133, accuracy: 13.14% |
| [2026-03-12 14:16:51 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [134/300] Train Time: 45.87s | Val Time: 14.17s |
| Train Acc: @1:72.52% @5:90.18% | Loss: 1.8440 |
| Val Acc: @1:13.43% @5:36.47% | Loss: 3.9606 |
| [2026-03-12 14:16:52 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 134, accuracy: 13.43% |
| [2026-03-12 14:17:57 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [135/300] Train Time: 45.91s | Val Time: 14.15s |
| Train Acc: @1:68.55% @5:89.98% | Loss: 1.9173 |
| Val Acc: @1:13.53% @5:36.76% | Loss: 3.9570 |
| [2026-03-12 14:18:03 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 135, accuracy: 13.53% |
| [2026-03-12 14:19:14 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [136/300] Train Time: 45.92s | Val Time: 14.32s |
| Train Acc: @1:70.44% @5:90.58% | Loss: 1.8865 |
| Val Acc: @1:13.53% @5:36.86% | Loss: 3.9535 |
| [2026-03-12 14:20:14 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [137/300] Train Time: 45.86s | Val Time: 14.16s |
| Train Acc: @1:69.84% @5:89.68% | Loss: 1.8835 |
| Val Acc: @1:13.53% @5:37.16% | Loss: 3.9500 |
| [2026-03-12 14:21:14 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [138/300] Train Time: 45.85s | Val Time: 14.07s |
| Train Acc: @1:72.72% @5:90.77% | Loss: 1.8106 |
| Val Acc: @1:13.73% @5:37.25% | Loss: 3.9462 |
| [2026-03-12 14:21:15 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 138, accuracy: 13.73% |
| [2026-03-12 14:22:22 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [139/300] Train Time: 45.71s | Val Time: 14.00s |
| Train Acc: @1:73.41% @5:91.07% | Loss: 1.8089 |
| Val Acc: @1:13.73% @5:37.55% | Loss: 3.9423 |
| [2026-03-12 14:23:22 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [140/300] Train Time: 45.66s | Val Time: 14.15s |
| Train Acc: @1:72.32% @5:90.97% | Loss: 1.8131 |
| Val Acc: @1:13.73% @5:37.84% | Loss: 3.9381 |
| [2026-03-12 14:24:33 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [141/300] Train Time: 45.73s | Val Time: 14.01s |
| Train Acc: @1:73.02% @5:91.37% | Loss: 1.7966 |
| Val Acc: @1:14.12% @5:37.94% | Loss: 3.9342 |
| [2026-03-12 14:24:33 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 141, accuracy: 14.12% |
| [2026-03-12 14:25:41 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [142/300] Train Time: 45.71s | Val Time: 14.00s |
| Train Acc: @1:76.39% @5:92.86% | Loss: 1.6992 |
| Val Acc: @1:14.31% @5:38.24% | Loss: 3.9305 |
| [2026-03-12 14:25:42 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 142, accuracy: 14.31% |
| [2026-03-12 14:26:54 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [143/300] Train Time: 46.35s | Val Time: 14.01s |
| Train Acc: @1:74.01% @5:90.18% | Loss: 1.7829 |
| Val Acc: @1:14.22% @5:38.33% | Loss: 3.9268 |
| [2026-03-12 14:27:54 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [144/300] Train Time: 45.65s | Val Time: 13.98s |
| Train Acc: @1:76.79% @5:91.07% | Loss: 1.7505 |
| Val Acc: @1:14.41% @5:38.43% | Loss: 3.9232 |
| [2026-03-12 14:27:55 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 144, accuracy: 14.41% |
| [2026-03-12 14:29:01 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [145/300] Train Time: 45.65s | Val Time: 14.05s |
| Train Acc: @1:75.30% @5:91.67% | Loss: 1.7378 |
| Val Acc: @1:14.41% @5:38.43% | Loss: 3.9197 |
| [2026-03-12 14:30:07 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [146/300] Train Time: 45.69s | Val Time: 14.03s |
| Train Acc: @1:74.01% @5:92.16% | Loss: 1.7457 |
| Val Acc: @1:14.61% @5:38.43% | Loss: 3.9162 |
| [2026-03-12 14:30:08 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 146, accuracy: 14.61% |
| [2026-03-12 14:31:14 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [147/300] Train Time: 45.67s | Val Time: 14.00s |
| Train Acc: @1:75.00% @5:91.77% | Loss: 1.7359 |
| Val Acc: @1:14.71% @5:38.43% | Loss: 3.9126 |
| [2026-03-12 14:31:15 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 147, accuracy: 14.71% |
| [2026-03-12 14:32:20 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [148/300] Train Time: 45.74s | Val Time: 14.01s |
| Train Acc: @1:77.18% @5:92.46% | Loss: 1.7158 |
| Val Acc: @1:14.61% @5:38.53% | Loss: 3.9090 |
| [2026-03-12 14:33:20 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [149/300] Train Time: 45.65s | Val Time: 14.01s |
| Train Acc: @1:77.68% @5:92.56% | Loss: 1.6718 |
| Val Acc: @1:14.90% @5:38.82% | Loss: 3.9055 |
| [2026-03-12 14:33:21 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 149, accuracy: 14.90% |
| [2026-03-12 14:34:27 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [150/300] Train Time: 45.63s | Val Time: 14.02s |
| Train Acc: @1:75.79% @5:92.56% | Loss: 1.7141 |
| Val Acc: @1:14.80% @5:39.22% | Loss: 3.9020 |
| [2026-03-12 14:35:32 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [151/300] Train Time: 45.61s | Val Time: 14.03s |
| Train Acc: @1:76.59% @5:92.36% | Loss: 1.6814 |
| Val Acc: @1:14.61% @5:39.80% | Loss: 3.8986 |
| [2026-03-12 14:36:32 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [152/300] Train Time: 45.68s | Val Time: 14.03s |
| Train Acc: @1:78.27% @5:93.25% | Loss: 1.6643 |
| Val Acc: @1:14.90% @5:40.00% | Loss: 3.8953 |
| [2026-03-12 14:37:33 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [153/300] Train Time: 45.67s | Val Time: 14.05s |
| Train Acc: @1:77.68% @5:92.86% | Loss: 1.6606 |
| Val Acc: @1:15.00% @5:40.00% | Loss: 3.8921 |
| [2026-03-12 14:37:33 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 153, accuracy: 15.00% |
| [2026-03-12 14:38:40 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [154/300] Train Time: 45.70s | Val Time: 14.02s |
| Train Acc: @1:78.47% @5:92.46% | Loss: 1.6522 |
| Val Acc: @1:15.10% @5:40.20% | Loss: 3.8888 |
| [2026-03-12 14:38:41 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 154, accuracy: 15.10% |
| [2026-03-12 14:39:47 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [155/300] Train Time: 45.71s | Val Time: 14.08s |
| Train Acc: @1:77.78% @5:92.86% | Loss: 1.6466 |
| Val Acc: @1:15.10% @5:40.29% | Loss: 3.8855 |
| [2026-03-12 14:40:54 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [156/300] Train Time: 45.71s | Val Time: 14.02s |
| Train Acc: @1:78.17% @5:92.96% | Loss: 1.6408 |
| Val Acc: @1:15.20% @5:40.59% | Loss: 3.8822 |
| [2026-03-12 14:40:55 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 156, accuracy: 15.20% |
| [2026-03-12 14:42:01 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [157/300] Train Time: 45.81s | Val Time: 14.01s |
| Train Acc: @1:76.98% @5:92.46% | Loss: 1.6571 |
| Val Acc: @1:15.39% @5:40.59% | Loss: 3.8788 |
| [2026-03-12 14:42:02 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 157, accuracy: 15.39% |
| [2026-03-12 14:43:09 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [158/300] Train Time: 45.68s | Val Time: 14.02s |
| Train Acc: @1:80.65% @5:92.36% | Loss: 1.6154 |
| Val Acc: @1:15.49% @5:40.69% | Loss: 3.8755 |
| [2026-03-12 14:43:10 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 158, accuracy: 15.49% |
| [2026-03-12 14:44:16 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [159/300] Train Time: 45.63s | Val Time: 14.03s |
| Train Acc: @1:80.95% @5:94.05% | Loss: 1.5832 |
| Val Acc: @1:15.59% @5:40.78% | Loss: 3.8723 |
| [2026-03-12 14:44:17 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 159, accuracy: 15.59% |
| [2026-03-12 14:45:23 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [160/300] Train Time: 45.66s | Val Time: 14.02s |
| Train Acc: @1:79.86% @5:93.85% | Loss: 1.5828 |
| Val Acc: @1:15.69% @5:40.88% | Loss: 3.8691 |
| [2026-03-12 14:45:30 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 160, accuracy: 15.69% |
| [2026-03-12 14:46:38 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [161/300] Train Time: 45.69s | Val Time: 14.02s |
| Train Acc: @1:80.26% @5:92.96% | Loss: 1.5853 |
| Val Acc: @1:15.98% @5:40.98% | Loss: 3.8661 |
| [2026-03-12 14:46:38 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 161, accuracy: 15.98% |
| [2026-03-12 14:47:47 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [162/300] Train Time: 45.67s | Val Time: 14.01s |
| Train Acc: @1:80.26% @5:94.15% | Loss: 1.5809 |
| Val Acc: @1:16.08% @5:41.18% | Loss: 3.8631 |
| [2026-03-12 14:47:48 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 162, accuracy: 16.08% |
| [2026-03-12 14:48:54 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [163/300] Train Time: 45.69s | Val Time: 14.02s |
| Train Acc: @1:80.46% @5:93.35% | Loss: 1.6039 |
| Val Acc: @1:15.98% @5:41.37% | Loss: 3.8600 |
| [2026-03-12 14:49:54 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [164/300] Train Time: 45.65s | Val Time: 14.03s |
| Train Acc: @1:81.15% @5:94.94% | Loss: 1.5374 |
| Val Acc: @1:16.08% @5:41.27% | Loss: 3.8571 |
| [2026-03-12 14:50:54 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [165/300] Train Time: 45.66s | Val Time: 14.02s |
| Train Acc: @1:81.15% @5:95.04% | Loss: 1.5635 |
| Val Acc: @1:16.37% @5:41.27% | Loss: 3.8542 |
| [2026-03-12 14:51:03 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 165, accuracy: 16.37% |
| [2026-03-12 14:52:12 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [166/300] Train Time: 45.68s | Val Time: 14.02s |
| Train Acc: @1:82.44% @5:94.64% | Loss: 1.5225 |
| Val Acc: @1:16.57% @5:41.37% | Loss: 3.8512 |
| [2026-03-12 14:52:12 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 166, accuracy: 16.57% |
| [2026-03-12 14:53:23 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [167/300] Train Time: 45.63s | Val Time: 14.03s |
| Train Acc: @1:81.75% @5:94.35% | Loss: 1.5085 |
| Val Acc: @1:16.76% @5:41.57% | Loss: 3.8482 |
| [2026-03-12 14:53:23 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 167, accuracy: 16.76% |
| [2026-03-12 14:54:30 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [168/300] Train Time: 45.64s | Val Time: 14.01s |
| Train Acc: @1:82.84% @5:95.73% | Loss: 1.4990 |
| Val Acc: @1:16.96% @5:41.67% | Loss: 3.8451 |
| [2026-03-12 14:54:31 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 168, accuracy: 16.96% |
| [2026-03-12 14:55:40 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [169/300] Train Time: 45.66s | Val Time: 14.01s |
| Train Acc: @1:84.23% @5:95.63% | Loss: 1.4784 |
| Val Acc: @1:16.76% @5:41.67% | Loss: 3.8421 |
| [2026-03-12 14:56:40 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [170/300] Train Time: 45.66s | Val Time: 14.03s |
| Train Acc: @1:83.73% @5:95.44% | Loss: 1.4592 |
| Val Acc: @1:16.86% @5:41.86% | Loss: 3.8390 |
| [2026-03-12 14:57:47 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [171/300] Train Time: 46.26s | Val Time: 14.03s |
| Train Acc: @1:83.43% @5:95.14% | Loss: 1.4919 |
| Val Acc: @1:17.25% @5:42.35% | Loss: 3.8361 |
| [2026-03-12 14:57:47 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 171, accuracy: 17.25% |
| [2026-03-12 14:58:53 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [172/300] Train Time: 45.67s | Val Time: 14.02s |
| Train Acc: @1:83.43% @5:95.14% | Loss: 1.4826 |
| Val Acc: @1:17.06% @5:42.35% | Loss: 3.8331 |
| [2026-03-12 14:59:53 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [173/300] Train Time: 45.63s | Val Time: 14.01s |
| Train Acc: @1:86.01% @5:96.13% | Loss: 1.4263 |
| Val Acc: @1:16.96% @5:42.94% | Loss: 3.8300 |
| [2026-03-12 15:00:53 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [174/300] Train Time: 45.69s | Val Time: 14.04s |
| Train Acc: @1:82.34% @5:93.95% | Loss: 1.5166 |
| Val Acc: @1:17.06% @5:43.04% | Loss: 3.8270 |
| [2026-03-12 15:01:53 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [175/300] Train Time: 45.67s | Val Time: 14.00s |
| Train Acc: @1:84.62% @5:94.94% | Loss: 1.4886 |
| Val Acc: @1:17.16% @5:42.94% | Loss: 3.8240 |
| [2026-03-12 15:03:00 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [176/300] Train Time: 45.68s | Val Time: 14.03s |
| Train Acc: @1:85.12% @5:95.73% | Loss: 1.4532 |
| Val Acc: @1:17.55% @5:43.24% | Loss: 3.8210 |
| [2026-03-12 15:03:01 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 176, accuracy: 17.55% |
| [2026-03-12 15:04:08 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [177/300] Train Time: 45.75s | Val Time: 14.05s |
| Train Acc: @1:84.72% @5:96.03% | Loss: 1.4669 |
| Val Acc: @1:17.65% @5:43.14% | Loss: 3.8182 |
| [2026-03-12 15:04:09 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 177, accuracy: 17.65% |
| [2026-03-12 15:05:16 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [178/300] Train Time: 45.73s | Val Time: 14.01s |
| Train Acc: @1:84.13% @5:95.73% | Loss: 1.4479 |
| Val Acc: @1:17.75% @5:43.14% | Loss: 3.8153 |
| [2026-03-12 15:05:17 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 178, accuracy: 17.75% |
| [2026-03-12 15:06:25 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [179/300] Train Time: 45.70s | Val Time: 14.02s |
| Train Acc: @1:84.42% @5:95.63% | Loss: 1.4470 |
| Val Acc: @1:17.94% @5:42.94% | Loss: 3.8123 |
| [2026-03-12 15:06:25 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 179, accuracy: 17.94% |
| [2026-03-12 15:07:45 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [180/300] Train Time: 45.69s | Val Time: 14.08s |
| Train Acc: @1:87.10% @5:96.63% | Loss: 1.3811 |
| Val Acc: @1:17.94% @5:43.14% | Loss: 3.8095 |
| [2026-03-12 15:08:54 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [181/300] Train Time: 45.71s | Val Time: 14.07s |
| Train Acc: @1:85.22% @5:95.24% | Loss: 1.4254 |
| Val Acc: @1:18.14% @5:43.24% | Loss: 3.8067 |
| [2026-03-12 15:08:55 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 181, accuracy: 18.14% |
| [2026-03-12 15:10:05 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [182/300] Train Time: 45.73s | Val Time: 14.02s |
| Train Acc: @1:86.31% @5:96.13% | Loss: 1.3779 |
| Val Acc: @1:18.24% @5:43.63% | Loss: 3.8040 |
| [2026-03-12 15:10:06 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 182, accuracy: 18.24% |
| [2026-03-12 15:11:18 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [183/300] Train Time: 45.66s | Val Time: 14.02s |
| Train Acc: @1:86.01% @5:96.13% | Loss: 1.4110 |
| Val Acc: @1:18.24% @5:43.73% | Loss: 3.8014 |
| [2026-03-12 15:12:18 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [184/300] Train Time: 45.65s | Val Time: 14.01s |
| Train Acc: @1:86.71% @5:96.33% | Loss: 1.3800 |
| Val Acc: @1:18.14% @5:43.92% | Loss: 3.7988 |
| [2026-03-12 15:13:18 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [185/300] Train Time: 45.67s | Val Time: 14.04s |
| Train Acc: @1:86.11% @5:95.73% | Loss: 1.3991 |
| Val Acc: @1:18.33% @5:44.31% | Loss: 3.7962 |
| [2026-03-12 15:13:25 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 185, accuracy: 18.33% |
| [2026-03-12 15:14:33 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [186/300] Train Time: 45.71s | Val Time: 14.02s |
| Train Acc: @1:83.83% @5:95.04% | Loss: 1.4420 |
| Val Acc: @1:18.33% @5:44.31% | Loss: 3.7935 |
| [2026-03-12 15:15:33 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [187/300] Train Time: 45.69s | Val Time: 14.11s |
| Train Acc: @1:87.70% @5:96.53% | Loss: 1.3503 |
| Val Acc: @1:18.33% @5:44.71% | Loss: 3.7909 |
| [2026-03-12 15:16:33 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [188/300] Train Time: 45.71s | Val Time: 14.04s |
| Train Acc: @1:86.31% @5:95.63% | Loss: 1.4086 |
| Val Acc: @1:18.33% @5:44.80% | Loss: 3.7883 |
| [2026-03-12 15:17:33 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [189/300] Train Time: 45.71s | Val Time: 14.04s |
| Train Acc: @1:88.10% @5:97.72% | Loss: 1.3216 |
| Val Acc: @1:18.43% @5:44.90% | Loss: 3.7857 |
| [2026-03-12 15:17:34 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 189, accuracy: 18.43% |
| [2026-03-12 15:18:38 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [190/300] Train Time: 45.72s | Val Time: 14.05s |
| Train Acc: @1:86.71% @5:95.44% | Loss: 1.3775 |
| Val Acc: @1:18.63% @5:44.90% | Loss: 3.7831 |
| [2026-03-12 15:18:44 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 190, accuracy: 18.63% |
| [2026-03-12 15:19:51 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [191/300] Train Time: 45.68s | Val Time: 14.05s |
| Train Acc: @1:88.39% @5:97.32% | Loss: 1.3149 |
| Val Acc: @1:18.73% @5:45.00% | Loss: 3.7805 |
| [2026-03-12 15:19:52 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 191, accuracy: 18.73% |
| [2026-03-12 15:20:57 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [192/300] Train Time: 45.73s | Val Time: 14.08s |
| Train Acc: @1:88.69% @5:97.42% | Loss: 1.3066 |
| Val Acc: @1:19.02% @5:45.20% | Loss: 3.7780 |
| [2026-03-12 15:20:57 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 192, accuracy: 19.02% |
| [2026-03-12 15:22:14 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [193/300] Train Time: 45.68s | Val Time: 14.06s |
| Train Acc: @1:88.59% @5:96.73% | Loss: 1.3213 |
| Val Acc: @1:19.02% @5:45.39% | Loss: 3.7754 |
| [2026-03-12 15:23:14 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [194/300] Train Time: 45.70s | Val Time: 14.04s |
| Train Acc: @1:89.48% @5:96.92% | Loss: 1.3213 |
| Val Acc: @1:18.92% @5:45.49% | Loss: 3.7729 |
| [2026-03-12 15:24:14 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [195/300] Train Time: 45.67s | Val Time: 14.02s |
| Train Acc: @1:89.88% @5:97.22% | Loss: 1.3030 |
| Val Acc: @1:18.92% @5:45.39% | Loss: 3.7703 |
| [2026-03-12 15:25:20 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [196/300] Train Time: 45.68s | Val Time: 14.02s |
| Train Acc: @1:89.48% @5:97.12% | Loss: 1.2987 |
| Val Acc: @1:18.82% @5:45.49% | Loss: 3.7678 |
| [2026-03-12 15:26:20 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [197/300] Train Time: 45.63s | Val Time: 14.11s |
| Train Acc: @1:91.87% @5:98.21% | Loss: 1.2569 |
| Val Acc: @1:19.02% @5:45.49% | Loss: 3.7653 |
| [2026-03-12 15:27:21 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [198/300] Train Time: 46.29s | Val Time: 14.02s |
| Train Acc: @1:89.38% @5:98.02% | Loss: 1.2853 |
| Val Acc: @1:19.02% @5:45.69% | Loss: 3.7629 |
| [2026-03-12 15:28:21 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [199/300] Train Time: 45.66s | Val Time: 14.02s |
| Train Acc: @1:88.49% @5:96.43% | Loss: 1.3189 |
| Val Acc: @1:19.22% @5:45.59% | Loss: 3.7604 |
| [2026-03-12 15:28:21 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 199, accuracy: 19.22% |
| [2026-03-12 15:29:26 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [200/300] Train Time: 45.67s | Val Time: 14.01s |
| Train Acc: @1:91.87% @5:97.62% | Loss: 1.2641 |
| Val Acc: @1:19.22% @5:45.69% | Loss: 3.7580 |
| [2026-03-12 15:30:30 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [201/300] Train Time: 45.62s | Val Time: 14.02s |
| Train Acc: @1:89.48% @5:97.62% | Loss: 1.2841 |
| Val Acc: @1:19.31% @5:45.69% | Loss: 3.7556 |
| [2026-03-12 15:30:31 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 201, accuracy: 19.31% |
| [2026-03-12 15:31:35 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [202/300] Train Time: 45.68s | Val Time: 14.03s |
| Train Acc: @1:91.27% @5:97.92% | Loss: 1.2396 |
| Val Acc: @1:19.31% @5:45.69% | Loss: 3.7532 |
| [2026-03-12 15:32:35 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [203/300] Train Time: 45.72s | Val Time: 14.02s |
| Train Acc: @1:88.79% @5:96.92% | Loss: 1.3214 |
| Val Acc: @1:19.22% @5:45.69% | Loss: 3.7510 |
| [2026-03-12 15:33:35 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [204/300] Train Time: 45.66s | Val Time: 14.02s |
| Train Acc: @1:90.28% @5:97.42% | Loss: 1.2645 |
| Val Acc: @1:19.51% @5:45.98% | Loss: 3.7487 |
| [2026-03-12 15:33:36 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 204, accuracy: 19.51% |
| [2026-03-12 15:34:40 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [205/300] Train Time: 45.62s | Val Time: 14.01s |
| Train Acc: @1:91.17% @5:97.92% | Loss: 1.2522 |
| Val Acc: @1:19.51% @5:45.69% | Loss: 3.7465 |
| [2026-03-12 15:35:45 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [206/300] Train Time: 45.63s | Val Time: 14.03s |
| Train Acc: @1:90.18% @5:97.52% | Loss: 1.2642 |
| Val Acc: @1:19.41% @5:45.88% | Loss: 3.7444 |
| [2026-03-12 15:36:45 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [207/300] Train Time: 45.68s | Val Time: 14.05s |
| Train Acc: @1:91.47% @5:97.82% | Loss: 1.2439 |
| Val Acc: @1:19.61% @5:45.98% | Loss: 3.7422 |
| [2026-03-12 15:36:46 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 207, accuracy: 19.61% |
| [2026-03-12 15:37:59 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [208/300] Train Time: 45.68s | Val Time: 14.01s |
| Train Acc: @1:90.18% @5:97.12% | Loss: 1.2634 |
| Val Acc: @1:19.71% @5:46.08% | Loss: 3.7400 |
| [2026-03-12 15:38:00 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 208, accuracy: 19.71% |
| [2026-03-12 15:39:15 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [209/300] Train Time: 45.71s | Val Time: 14.00s |
| Train Acc: @1:92.36% @5:98.02% | Loss: 1.1896 |
| Val Acc: @1:19.71% @5:46.18% | Loss: 3.7379 |
| [2026-03-12 15:40:15 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [210/300] Train Time: 45.67s | Val Time: 14.06s |
| Train Acc: @1:91.67% @5:98.02% | Loss: 1.2257 |
| Val Acc: @1:19.80% @5:46.08% | Loss: 3.7357 |
| [2026-03-12 15:40:21 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 210, accuracy: 19.80% |
| [2026-03-12 15:41:27 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [211/300] Train Time: 45.73s | Val Time: 14.05s |
| Train Acc: @1:92.66% @5:98.41% | Loss: 1.2125 |
| Val Acc: @1:19.90% @5:46.18% | Loss: 3.7335 |
| [2026-03-12 15:41:27 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 211, accuracy: 19.90% |
| [2026-03-12 15:42:32 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [212/300] Train Time: 45.69s | Val Time: 14.05s |
| Train Acc: @1:92.66% @5:98.81% | Loss: 1.1943 |
| Val Acc: @1:20.00% @5:46.37% | Loss: 3.7314 |
| [2026-03-12 15:42:32 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 212, accuracy: 20.00% |
| [2026-03-12 15:43:37 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [213/300] Train Time: 45.70s | Val Time: 14.02s |
| Train Acc: @1:92.36% @5:97.52% | Loss: 1.2168 |
| Val Acc: @1:20.10% @5:46.27% | Loss: 3.7292 |
| [2026-03-12 15:43:37 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 213, accuracy: 20.10% |
| [2026-03-12 15:44:42 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [214/300] Train Time: 45.72s | Val Time: 14.03s |
| Train Acc: @1:92.66% @5:98.61% | Loss: 1.2160 |
| Val Acc: @1:20.20% @5:46.18% | Loss: 3.7270 |
| [2026-03-12 15:44:42 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 214, accuracy: 20.20% |
| [2026-03-12 15:45:47 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [215/300] Train Time: 45.69s | Val Time: 14.04s |
| Train Acc: @1:92.36% @5:98.91% | Loss: 1.1866 |
| Val Acc: @1:20.39% @5:46.27% | Loss: 3.7248 |
| [2026-03-12 15:45:53 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 215, accuracy: 20.39% |
| [2026-03-12 15:46:59 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [216/300] Train Time: 45.80s | Val Time: 14.10s |
| Train Acc: @1:92.66% @5:98.12% | Loss: 1.1925 |
| Val Acc: @1:20.59% @5:46.57% | Loss: 3.7227 |
| [2026-03-12 15:47:00 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 216, accuracy: 20.59% |
| [2026-03-12 15:48:05 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [217/300] Train Time: 45.86s | Val Time: 14.03s |
| Train Acc: @1:93.45% @5:98.51% | Loss: 1.1818 |
| Val Acc: @1:20.78% @5:46.57% | Loss: 3.7205 |
| [2026-03-12 15:48:05 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 217, accuracy: 20.78% |
| [2026-03-12 15:49:10 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [218/300] Train Time: 45.69s | Val Time: 14.02s |
| Train Acc: @1:92.16% @5:98.31% | Loss: 1.2030 |
| Val Acc: @1:20.88% @5:46.76% | Loss: 3.7183 |
| [2026-03-12 15:49:11 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 218, accuracy: 20.88% |
| [2026-03-12 15:50:15 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [219/300] Train Time: 45.69s | Val Time: 14.03s |
| Train Acc: @1:91.87% @5:97.62% | Loss: 1.2183 |
| Val Acc: @1:20.98% @5:46.57% | Loss: 3.7162 |
| [2026-03-12 15:50:16 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 219, accuracy: 20.98% |
| [2026-03-12 15:51:21 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [220/300] Train Time: 45.65s | Val Time: 14.03s |
| Train Acc: @1:95.04% @5:98.71% | Loss: 1.1518 |
| Val Acc: @1:21.08% @5:46.67% | Loss: 3.7142 |
| [2026-03-12 15:51:26 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 220, accuracy: 21.08% |
| [2026-03-12 15:52:32 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [221/300] Train Time: 45.73s | Val Time: 14.01s |
| Train Acc: @1:92.36% @5:98.41% | Loss: 1.2082 |
| Val Acc: @1:21.18% @5:46.86% | Loss: 3.7121 |
| [2026-03-12 15:52:33 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 221, accuracy: 21.18% |
| [2026-03-12 15:53:37 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [222/300] Train Time: 45.71s | Val Time: 14.02s |
| Train Acc: @1:93.65% @5:98.21% | Loss: 1.1801 |
| Val Acc: @1:21.18% @5:46.96% | Loss: 3.7101 |
| [2026-03-12 15:54:37 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [223/300] Train Time: 45.71s | Val Time: 14.03s |
| Train Acc: @1:94.15% @5:98.71% | Loss: 1.1560 |
| Val Acc: @1:21.47% @5:46.96% | Loss: 3.7080 |
| [2026-03-12 15:54:38 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 223, accuracy: 21.47% |
| [2026-03-12 15:55:42 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [224/300] Train Time: 45.70s | Val Time: 13.99s |
| Train Acc: @1:93.95% @5:98.12% | Loss: 1.1636 |
| Val Acc: @1:21.57% @5:47.06% | Loss: 3.7059 |
| [2026-03-12 15:55:43 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 224, accuracy: 21.57% |
| [2026-03-12 15:56:48 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [225/300] Train Time: 45.69s | Val Time: 14.06s |
| Train Acc: @1:93.35% @5:98.61% | Loss: 1.1721 |
| Val Acc: @1:21.57% @5:46.96% | Loss: 3.7038 |
| [2026-03-12 15:57:54 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [226/300] Train Time: 45.68s | Val Time: 14.02s |
| Train Acc: @1:93.95% @5:98.51% | Loss: 1.1634 |
| Val Acc: @1:21.57% @5:46.96% | Loss: 3.7017 |
| [2026-03-12 15:58:54 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [227/300] Train Time: 45.67s | Val Time: 14.04s |
| Train Acc: @1:92.16% @5:98.31% | Loss: 1.1891 |
| Val Acc: @1:21.76% @5:47.16% | Loss: 3.6997 |
| [2026-03-12 15:58:55 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 227, accuracy: 21.76% |
| [2026-03-12 16:00:01 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [228/300] Train Time: 45.67s | Val Time: 14.12s |
| Train Acc: @1:93.25% @5:98.71% | Loss: 1.1451 |
| Val Acc: @1:22.06% @5:47.25% | Loss: 3.6977 |
| [2026-03-12 16:00:01 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 228, accuracy: 22.06% |
| [2026-03-12 16:01:09 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [229/300] Train Time: 45.69s | Val Time: 14.03s |
| Train Acc: @1:95.14% @5:98.51% | Loss: 1.1220 |
| Val Acc: @1:22.06% @5:47.35% | Loss: 3.6957 |
| [2026-03-12 16:02:09 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [230/300] Train Time: 45.60s | Val Time: 14.02s |
| Train Acc: @1:94.64% @5:98.61% | Loss: 1.1554 |
| Val Acc: @1:22.06% @5:47.25% | Loss: 3.6937 |
| [2026-03-12 16:03:15 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [231/300] Train Time: 45.77s | Val Time: 14.06s |
| Train Acc: @1:93.35% @5:98.61% | Loss: 1.1719 |
| Val Acc: @1:21.96% @5:47.25% | Loss: 3.6918 |
| [2026-03-12 16:04:15 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [232/300] Train Time: 45.63s | Val Time: 14.06s |
| Train Acc: @1:95.04% @5:98.91% | Loss: 1.1274 |
| Val Acc: @1:21.96% @5:46.96% | Loss: 3.6898 |
| [2026-03-12 16:05:16 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [233/300] Train Time: 45.69s | Val Time: 14.01s |
| Train Acc: @1:95.54% @5:99.11% | Loss: 1.1167 |
| Val Acc: @1:21.96% @5:47.06% | Loss: 3.6878 |
| [2026-03-12 16:06:16 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [234/300] Train Time: 45.66s | Val Time: 14.01s |
| Train Acc: @1:94.74% @5:98.12% | Loss: 1.1485 |
| Val Acc: @1:22.16% @5:47.06% | Loss: 3.6859 |
| [2026-03-12 16:06:16 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 234, accuracy: 22.16% |
| [2026-03-12 16:07:22 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [235/300] Train Time: 45.70s | Val Time: 14.03s |
| Train Acc: @1:94.64% @5:98.91% | Loss: 1.1343 |
| Val Acc: @1:21.86% @5:47.35% | Loss: 3.6839 |
| [2026-03-12 16:08:27 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [236/300] Train Time: 45.69s | Val Time: 14.03s |
| Train Acc: @1:94.44% @5:99.11% | Loss: 1.1252 |
| Val Acc: @1:21.76% @5:47.25% | Loss: 3.6819 |
| [2026-03-12 16:09:28 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [237/300] Train Time: 45.71s | Val Time: 14.09s |
| Train Acc: @1:94.74% @5:98.81% | Loss: 1.1504 |
| Val Acc: @1:21.86% @5:47.55% | Loss: 3.6799 |
| [2026-03-12 16:10:28 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [238/300] Train Time: 45.72s | Val Time: 14.05s |
| Train Acc: @1:95.63% @5:99.01% | Loss: 1.1066 |
| Val Acc: @1:22.25% @5:47.75% | Loss: 3.6780 |
| [2026-03-12 16:10:28 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 238, accuracy: 22.25% |
| [2026-03-12 16:11:37 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [239/300] Train Time: 45.66s | Val Time: 14.04s |
| Train Acc: @1:95.24% @5:99.11% | Loss: 1.1264 |
| Val Acc: @1:22.35% @5:47.75% | Loss: 3.6761 |
| [2026-03-12 16:11:37 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 239, accuracy: 22.35% |
| [2026-03-12 16:12:47 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [240/300] Train Time: 45.66s | Val Time: 14.05s |
| Train Acc: @1:94.94% @5:99.11% | Loss: 1.1143 |
| Val Acc: @1:22.45% @5:47.84% | Loss: 3.6743 |
| [2026-03-12 16:12:57 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 240, accuracy: 22.45% |
| [2026-03-12 16:14:04 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [241/300] Train Time: 45.65s | Val Time: 14.01s |
| Train Acc: @1:95.34% @5:99.01% | Loss: 1.1101 |
| Val Acc: @1:22.55% @5:47.94% | Loss: 3.6724 |
| [2026-03-12 16:14:04 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 241, accuracy: 22.55% |
| [2026-03-12 16:15:10 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [242/300] Train Time: 45.72s | Val Time: 14.04s |
| Train Acc: @1:94.15% @5:98.21% | Loss: 1.1399 |
| Val Acc: @1:22.75% @5:48.04% | Loss: 3.6706 |
| [2026-03-12 16:15:11 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 242, accuracy: 22.75% |
| [2026-03-12 16:16:19 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [243/300] Train Time: 45.69s | Val Time: 14.03s |
| Train Acc: @1:94.84% @5:98.71% | Loss: 1.1353 |
| Val Acc: @1:22.65% @5:48.24% | Loss: 3.6687 |
| [2026-03-12 16:17:19 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [244/300] Train Time: 45.71s | Val Time: 14.03s |
| Train Acc: @1:94.25% @5:98.91% | Loss: 1.1165 |
| Val Acc: @1:22.65% @5:48.33% | Loss: 3.6669 |
| [2026-03-12 16:18:19 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [245/300] Train Time: 45.70s | Val Time: 14.03s |
| Train Acc: @1:94.94% @5:99.01% | Loss: 1.1140 |
| Val Acc: @1:22.75% @5:48.43% | Loss: 3.6650 |
| [2026-03-12 16:19:29 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [246/300] Train Time: 45.66s | Val Time: 14.08s |
| Train Acc: @1:94.54% @5:98.31% | Loss: 1.1375 |
| Val Acc: @1:22.75% @5:48.53% | Loss: 3.6632 |
| [2026-03-12 16:20:29 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [247/300] Train Time: 45.68s | Val Time: 14.01s |
| Train Acc: @1:96.23% @5:98.81% | Loss: 1.0930 |
| Val Acc: @1:22.75% @5:48.53% | Loss: 3.6614 |
| [2026-03-12 16:21:29 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [248/300] Train Time: 45.69s | Val Time: 14.04s |
| Train Acc: @1:94.15% @5:99.11% | Loss: 1.1100 |
| Val Acc: @1:22.94% @5:48.73% | Loss: 3.6597 |
| [2026-03-12 16:21:29 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 248, accuracy: 22.94% |
| [2026-03-12 16:22:39 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [249/300] Train Time: 45.66s | Val Time: 14.04s |
| Train Acc: @1:94.64% @5:98.61% | Loss: 1.1178 |
| Val Acc: @1:23.33% @5:48.82% | Loss: 3.6579 |
| [2026-03-12 16:22:40 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 249, accuracy: 23.33% |
| [2026-03-12 16:23:50 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [250/300] Train Time: 45.67s | Val Time: 14.05s |
| Train Acc: @1:94.44% @5:99.11% | Loss: 1.1192 |
| Val Acc: @1:23.43% @5:48.73% | Loss: 3.6561 |
| [2026-03-12 16:23:58 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 250, accuracy: 23.43% |
| [2026-03-12 16:25:07 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [251/300] Train Time: 45.69s | Val Time: 14.05s |
| Train Acc: @1:95.93% @5:98.91% | Loss: 1.0905 |
| Val Acc: @1:23.43% @5:48.63% | Loss: 3.6542 |
| [2026-03-12 16:26:08 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [252/300] Train Time: 45.67s | Val Time: 14.08s |
| Train Acc: @1:95.73% @5:98.71% | Loss: 1.0983 |
| Val Acc: @1:23.43% @5:48.82% | Loss: 3.6525 |
| [2026-03-12 16:27:08 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [253/300] Train Time: 45.72s | Val Time: 14.05s |
| Train Acc: @1:94.35% @5:98.81% | Loss: 1.1292 |
| Val Acc: @1:23.33% @5:48.92% | Loss: 3.6507 |
| [2026-03-12 16:28:08 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [254/300] Train Time: 45.63s | Val Time: 14.06s |
| Train Acc: @1:93.95% @5:98.81% | Loss: 1.1338 |
| Val Acc: @1:23.43% @5:49.02% | Loss: 3.6489 |
| [2026-03-12 16:29:08 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [255/300] Train Time: 45.66s | Val Time: 14.05s |
| Train Acc: @1:95.24% @5:99.21% | Loss: 1.1105 |
| Val Acc: @1:23.53% @5:49.22% | Loss: 3.6471 |
| [2026-03-12 16:29:16 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 255, accuracy: 23.53% |
| [2026-03-12 16:30:25 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [256/300] Train Time: 45.74s | Val Time: 14.12s |
| Train Acc: @1:95.73% @5:99.31% | Loss: 1.0931 |
| Val Acc: @1:23.53% @5:49.12% | Loss: 3.6452 |
| [2026-03-12 16:31:25 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [257/300] Train Time: 45.88s | Val Time: 14.04s |
| Train Acc: @1:95.14% @5:99.11% | Loss: 1.0917 |
| Val Acc: @1:23.43% @5:49.22% | Loss: 3.6434 |
| [2026-03-12 16:32:25 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [258/300] Train Time: 45.69s | Val Time: 14.04s |
| Train Acc: @1:95.24% @5:98.41% | Loss: 1.1202 |
| Val Acc: @1:23.43% @5:49.31% | Loss: 3.6417 |
| [2026-03-12 16:33:25 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [259/300] Train Time: 45.68s | Val Time: 14.03s |
| Train Acc: @1:95.63% @5:99.50% | Loss: 1.0971 |
| Val Acc: @1:23.73% @5:49.41% | Loss: 3.6399 |
| [2026-03-12 16:33:26 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 259, accuracy: 23.73% |
| [2026-03-12 16:34:31 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [260/300] Train Time: 45.70s | Val Time: 14.06s |
| Train Acc: @1:94.94% @5:99.40% | Loss: 1.0991 |
| Val Acc: @1:23.73% @5:49.51% | Loss: 3.6382 |
| [2026-03-12 16:35:38 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [261/300] Train Time: 45.71s | Val Time: 14.06s |
| Train Acc: @1:94.64% @5:98.41% | Loss: 1.1200 |
| Val Acc: @1:23.63% @5:49.61% | Loss: 3.6364 |
| [2026-03-12 16:36:38 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [262/300] Train Time: 45.63s | Val Time: 14.06s |
| Train Acc: @1:93.95% @5:98.61% | Loss: 1.1255 |
| Val Acc: @1:23.53% @5:49.71% | Loss: 3.6347 |
| [2026-03-12 16:37:38 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [263/300] Train Time: 45.70s | Val Time: 14.05s |
| Train Acc: @1:96.53% @5:99.11% | Loss: 1.0912 |
| Val Acc: @1:23.43% @5:49.61% | Loss: 3.6329 |
| [2026-03-12 16:38:38 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [264/300] Train Time: 45.71s | Val Time: 14.10s |
| Train Acc: @1:96.13% @5:99.21% | Loss: 1.0902 |
| Val Acc: @1:23.43% @5:49.71% | Loss: 3.6311 |
| [2026-03-12 16:39:38 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [265/300] Train Time: 45.66s | Val Time: 14.18s |
| Train Acc: @1:94.35% @5:99.31% | Loss: 1.1096 |
| Val Acc: @1:23.53% @5:49.80% | Loss: 3.6294 |
| [2026-03-12 16:40:45 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [266/300] Train Time: 45.68s | Val Time: 14.11s |
| Train Acc: @1:94.74% @5:98.91% | Loss: 1.1030 |
| Val Acc: @1:23.63% @5:49.80% | Loss: 3.6276 |
| [2026-03-12 16:41:45 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [267/300] Train Time: 45.73s | Val Time: 14.04s |
| Train Acc: @1:94.94% @5:98.81% | Loss: 1.1190 |
| Val Acc: @1:24.12% @5:49.90% | Loss: 3.6258 |
| [2026-03-12 16:41:45 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 267, accuracy: 24.12% |
| [2026-03-12 16:42:51 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [268/300] Train Time: 45.71s | Val Time: 14.04s |
| Train Acc: @1:96.53% @5:99.31% | Loss: 1.0743 |
| Val Acc: @1:24.12% @5:49.90% | Loss: 3.6241 |
| [2026-03-12 16:43:51 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [269/300] Train Time: 45.69s | Val Time: 14.03s |
| Train Acc: @1:95.24% @5:98.02% | Loss: 1.1202 |
| Val Acc: @1:24.22% @5:50.10% | Loss: 3.6223 |
| [2026-03-12 16:43:52 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 269, accuracy: 24.22% |
| [2026-03-12 16:44:58 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [270/300] Train Time: 45.71s | Val Time: 14.03s |
| Train Acc: @1:95.73% @5:98.81% | Loss: 1.0947 |
| Val Acc: @1:24.41% @5:50.20% | Loss: 3.6206 |
| [2026-03-12 16:45:07 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 270, accuracy: 24.41% |
| [2026-03-12 16:46:15 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [271/300] Train Time: 45.73s | Val Time: 14.06s |
| Train Acc: @1:94.94% @5:98.71% | Loss: 1.1123 |
| Val Acc: @1:24.51% @5:50.29% | Loss: 3.6189 |
| [2026-03-12 16:46:16 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 271, accuracy: 24.51% |
| [2026-03-12 16:47:22 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [272/300] Train Time: 45.72s | Val Time: 14.05s |
| Train Acc: @1:95.63% @5:99.21% | Loss: 1.0963 |
| Val Acc: @1:24.31% @5:50.29% | Loss: 3.6172 |
| [2026-03-12 16:48:22 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [273/300] Train Time: 45.68s | Val Time: 14.04s |
| Train Acc: @1:95.34% @5:98.71% | Loss: 1.1034 |
| Val Acc: @1:24.31% @5:50.39% | Loss: 3.6155 |
| [2026-03-12 16:49:22 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [274/300] Train Time: 45.70s | Val Time: 14.02s |
| Train Acc: @1:95.44% @5:98.61% | Loss: 1.0935 |
| Val Acc: @1:24.31% @5:50.78% | Loss: 3.6137 |
| [2026-03-12 16:50:22 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [275/300] Train Time: 45.64s | Val Time: 14.03s |
| Train Acc: @1:96.33% @5:99.31% | Loss: 1.0808 |
| Val Acc: @1:24.22% @5:50.49% | Loss: 3.6120 |
| [2026-03-12 16:51:28 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [276/300] Train Time: 45.71s | Val Time: 14.12s |
| Train Acc: @1:95.63% @5:98.91% | Loss: 1.1139 |
| Val Acc: @1:24.22% @5:50.39% | Loss: 3.6103 |
| [2026-03-12 16:52:28 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [277/300] Train Time: 45.67s | Val Time: 14.04s |
| Train Acc: @1:95.73% @5:98.91% | Loss: 1.1025 |
| Val Acc: @1:24.31% @5:50.49% | Loss: 3.6086 |
| [2026-03-12 16:53:28 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [278/300] Train Time: 45.71s | Val Time: 14.07s |
| Train Acc: @1:95.54% @5:99.40% | Loss: 1.0819 |
| Val Acc: @1:24.31% @5:50.49% | Loss: 3.6069 |
| [2026-03-12 16:54:28 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [279/300] Train Time: 45.72s | Val Time: 14.07s |
| Train Acc: @1:95.73% @5:99.11% | Loss: 1.0784 |
| Val Acc: @1:24.31% @5:50.39% | Loss: 3.6052 |
| [2026-03-12 16:55:28 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [280/300] Train Time: 45.67s | Val Time: 14.08s |
| Train Acc: @1:95.04% @5:99.21% | Loss: 1.0922 |
| Val Acc: @1:24.51% @5:50.39% | Loss: 3.6036 |
| [2026-03-12 16:56:35 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [281/300] Train Time: 45.70s | Val Time: 14.03s |
| Train Acc: @1:96.33% @5:99.60% | Loss: 1.0853 |
| Val Acc: @1:24.71% @5:50.59% | Loss: 3.6019 |
| [2026-03-12 16:56:35 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 281, accuracy: 24.71% |
| [2026-03-12 16:57:45 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [282/300] Train Time: 45.70s | Val Time: 14.04s |
| Train Acc: @1:95.34% @5:99.21% | Loss: 1.0946 |
| Val Acc: @1:24.71% @5:50.69% | Loss: 3.6002 |
| [2026-03-12 16:58:46 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [283/300] Train Time: 46.77s | Val Time: 14.20s |
| Train Acc: @1:96.63% @5:99.11% | Loss: 1.0794 |
| Val Acc: @1:24.71% @5:50.78% | Loss: 3.5985 |
| [2026-03-12 16:59:46 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [284/300] Train Time: 45.63s | Val Time: 14.04s |
| Train Acc: @1:94.54% @5:99.11% | Loss: 1.1074 |
| Val Acc: @1:24.71% @5:50.69% | Loss: 3.5968 |
| [2026-03-12 17:00:46 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [285/300] Train Time: 45.69s | Val Time: 14.04s |
| Train Acc: @1:96.73% @5:99.50% | Loss: 1.0633 |
| Val Acc: @1:24.71% @5:50.59% | Loss: 3.5951 |
| [2026-03-12 17:01:52 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [286/300] Train Time: 45.69s | Val Time: 14.05s |
| Train Acc: @1:96.03% @5:99.01% | Loss: 1.0861 |
| Val Acc: @1:24.80% @5:50.59% | Loss: 3.5934 |
| [2026-03-12 17:01:53 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 286, accuracy: 24.80% |
| [2026-03-12 17:02:58 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [287/300] Train Time: 45.75s | Val Time: 14.07s |
| Train Acc: @1:94.94% @5:99.01% | Loss: 1.0871 |
| Val Acc: @1:24.80% @5:50.88% | Loss: 3.5918 |
| [2026-03-12 17:03:58 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [288/300] Train Time: 45.63s | Val Time: 14.08s |
| Train Acc: @1:95.34% @5:99.21% | Loss: 1.1056 |
| Val Acc: @1:24.90% @5:50.78% | Loss: 3.5901 |
| [2026-03-12 17:03:59 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 288, accuracy: 24.90% |
| [2026-03-12 17:05:04 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [289/300] Train Time: 45.71s | Val Time: 14.04s |
| Train Acc: @1:95.73% @5:99.40% | Loss: 1.0860 |
| Val Acc: @1:24.80% @5:50.98% | Loss: 3.5884 |
| [2026-03-12 17:06:04 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [290/300] Train Time: 45.74s | Val Time: 14.05s |
| Train Acc: @1:95.24% @5:99.11% | Loss: 1.1084 |
| Val Acc: @1:24.90% @5:50.88% | Loss: 3.5867 |
| [2026-03-12 17:07:12 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [291/300] Train Time: 45.66s | Val Time: 14.05s |
| Train Acc: @1:95.63% @5:98.91% | Loss: 1.1045 |
| Val Acc: @1:24.90% @5:50.98% | Loss: 3.5851 |
| [2026-03-12 17:08:12 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [292/300] Train Time: 45.69s | Val Time: 14.06s |
| Train Acc: @1:95.93% @5:99.31% | Loss: 1.0808 |
| Val Acc: @1:25.10% @5:50.98% | Loss: 3.5834 |
| [2026-03-12 17:08:13 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 292, accuracy: 25.10% |
| [2026-03-12 17:09:18 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [293/300] Train Time: 45.69s | Val Time: 14.08s |
| Train Acc: @1:94.74% @5:98.91% | Loss: 1.1029 |
| Val Acc: @1:25.39% @5:50.98% | Loss: 3.5817 |
| [2026-03-12 17:09:19 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 293, accuracy: 25.39% |
| [2026-03-12 17:10:24 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [294/300] Train Time: 45.70s | Val Time: 14.04s |
| Train Acc: @1:96.53% @5:99.40% | Loss: 1.0608 |
| Val Acc: @1:25.59% @5:51.08% | Loss: 3.5800 |
| [2026-03-12 17:10:25 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 294, accuracy: 25.59% |
| [2026-03-12 17:11:34 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [295/300] Train Time: 45.71s | Val Time: 14.08s |
| Train Acc: @1:95.73% @5:99.31% | Loss: 1.0925 |
| Val Acc: @1:25.59% @5:51.18% | Loss: 3.5783 |
| [2026-03-12 17:12:42 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [296/300] Train Time: 45.66s | Val Time: 14.06s |
| Train Acc: @1:96.33% @5:99.70% | Loss: 1.0648 |
| Val Acc: @1:25.59% @5:51.08% | Loss: 3.5767 |
| [2026-03-12 17:13:43 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [297/300] Train Time: 45.80s | Val Time: 14.05s |
| Train Acc: @1:95.63% @5:99.01% | Loss: 1.0959 |
| Val Acc: @1:25.98% @5:51.18% | Loss: 3.5750 |
| [2026-03-12 17:13:43 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 297, accuracy: 25.98% |
| [2026-03-12 17:14:51 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [298/300] Train Time: 45.77s | Val Time: 14.04s |
| Train Acc: @1:96.23% @5:98.91% | Loss: 1.0813 |
| Val Acc: @1:25.98% @5:51.27% | Loss: 3.5734 |
| [2026-03-12 17:15:52 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [299/300] Train Time: 45.70s | Val Time: 14.09s |
| Train Acc: @1:95.63% @5:98.81% | Loss: 1.0882 |
| Val Acc: @1:26.08% @5:51.37% | Loss: 3.5717 |
| [2026-03-12 17:15:52 LinearSpectre] (70562186.py 126): INFO 🔥 Best checkpoint saved at epoch 299, accuracy: 26.08% |
| [2026-03-12 17:17:06 LinearSpectre] (70562186.py 104): INFO |
| ViG Epoch [300/300] Train Time: 45.80s | Val Time: 14.05s |
| Train Acc: @1:96.03% @5:99.21% | Loss: 1.1009 |
| Val Acc: @1:26.08% @5:51.37% | Loss: 3.5700 |
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