Datasets:
trackio
/
documentation_dataset

Dataset card Data Studio Files
xet
Community
1
id
int64
1
28
timestamp
stringdate
2025-07-29 20:12:19
2025-07-29 20:12:50
run_name
stringclasses
2 values
step
int64
0
19
metrics
stringlengths
90
92
1
2025-07-29T20:12:19.149381
test-run-1
0
{"train_loss": 0.1814, "train_accuracy": 0.7199, "val_loss": 0.8897, "val_accuracy": 0.6241}
2
2025-07-29T20:12:20.195831
test-run-1
1
{"train_loss": 0.6286, "train_accuracy": 0.8083, "val_loss": 0.7736, "val_accuracy": 0.7905}
3
2025-07-29T20:12:21.541607
test-run-1
2
{"train_loss": 0.381, "train_accuracy": 0.8027, "val_loss": 0.5944, "val_accuracy": 0.853}
4
2025-07-29T20:12:22.684761
test-run-1
3
{"train_loss": 0.3383, "train_accuracy": 0.73, "val_loss": 0.2871, "val_accuracy": 0.7091}
5
2025-07-29T20:12:23.937195
test-run-1
4
{"train_loss": 0.5213, "train_accuracy": 0.8465, "val_loss": 0.5813, "val_accuracy": 0.8015}
6
2025-07-29T20:12:25.142865
test-run-1
5
{"train_loss": 0.2117, "train_accuracy": 0.7627, "val_loss": 0.1501, "val_accuracy": 0.7654}
7
2025-07-29T20:12:26.327692
test-run-1
6
{"train_loss": 0.3256, "train_accuracy": 0.8433, "val_loss": 0.2496, "val_accuracy": 0.8525}
8
2025-07-29T20:12:27.472154
test-run-1
7
{"train_loss": 0.2479, "train_accuracy": 0.795, "val_loss": 0.0391, "val_accuracy": 0.7618}
9
2025-07-29T20:12:29.491798
test-run-2
0
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10
2025-07-29T20:12:30.153500
test-run-2
1
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11
2025-07-29T20:12:30.743374
test-run-2
2
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12
2025-07-29T20:12:32.013766
test-run-2
3
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13
2025-07-29T20:12:33.133102
test-run-2
4
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14
2025-07-29T20:12:34.288951
test-run-2
5
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15
2025-07-29T20:12:35.417501
test-run-2
6
{"train_loss": 1.5158, "train_accuracy": 0.2661, "val_loss": 2.0111, "val_accuracy": 0.4374}
16
2025-07-29T20:12:36.572166
test-run-2
7
{"train_loss": 1.4133, "train_accuracy": 0.3513, "val_loss": 0.8965, "val_accuracy": 0.2597}
17
2025-07-29T20:12:37.683990
test-run-2
8
{"train_loss": 1.0256, "train_accuracy": 0.3766, "val_loss": 1.1814, "val_accuracy": 0.6217}
18
2025-07-29T20:12:38.907112
test-run-2
9
{"train_loss": 0.9068, "train_accuracy": 0.6241, "val_loss": 0.8049, "val_accuracy": 0.5256}
19
2025-07-29T20:12:40.063347
test-run-2
10
{"train_loss": 0.83, "train_accuracy": 0.5868, "val_loss": 0.7022, "val_accuracy": 0.5781}
20
2025-07-29T20:12:41.278464
test-run-2
11
{"train_loss": 0.6475, "train_accuracy": 0.6375, "val_loss": 0.4596, "val_accuracy": 0.6379}
21
2025-07-29T20:12:42.408693
test-run-2
12
{"train_loss": 0.509, "train_accuracy": 0.896, "val_loss": 0.5365, "val_accuracy": 0.6813}
22
2025-07-29T20:12:43.672907
test-run-2
13
{"train_loss": 0.2753, "train_accuracy": 0.723, "val_loss": 0.5922, "val_accuracy": 0.8551}
23
2025-07-29T20:12:44.832586
test-run-2
14
{"train_loss": 0.4897, "train_accuracy": 0.8376, "val_loss": 0.4946, "val_accuracy": 0.7926}
24
2025-07-29T20:12:46.002652
test-run-2
15
{"train_loss": 0.2708, "train_accuracy": 0.7416, "val_loss": 0.5497, "val_accuracy": 0.7613}
25
2025-07-29T20:12:47.116098
test-run-2
16
{"train_loss": 0.4772, "train_accuracy": 0.755, "val_loss": 0.2859, "val_accuracy": 0.7946}
26
2025-07-29T20:12:48.291993
test-run-2
17
{"train_loss": 0.4417, "train_accuracy": 0.8282, "val_loss": 0.0453, "val_accuracy": 0.7405}
27
2025-07-29T20:12:49.391499
test-run-2
18
{"train_loss": 0.2871, "train_accuracy": 0.8184, "val_loss": 0.4232, "val_accuracy": 0.7608}
28
2025-07-29T20:12:50.548949
test-run-2
19
{"train_loss": 0.2244, "train_accuracy": 0.7493, "val_loss": 0.5048, "val_accuracy": 0.8436}