add s222_resnet50
Browse files- seed-222/uasyaxra-s222_resnet50/metadata.yml +40 -0
- seed-222/uasyaxra-s222_resnet50/model_epoch_30_f1_0.6243.pth +3 -0
- seed-222/uasyaxra-s222_resnet50/model_epoch_31_accuracy_0.6612.pth +3 -0
- seed-222/uasyaxra-s222_resnet50/model_epoch_31_f1_0.6280.pth +3 -0
- seed-222/uasyaxra-s222_resnet50/model_epoch_33_accuracy_0.6582.pth +3 -0
- seed-222/uasyaxra-s222_resnet50/model_epoch_33_f1_0.6251.pth +3 -0
- seed-222/uasyaxra-s222_resnet50/model_epoch_35_accuracy_0.6597.pth +3 -0
- seed-222/uasyaxra-s222_resnet50/model_epoch_35_f1_0.6286.pth +3 -0
- seed-222/uasyaxra-s222_resnet50/model_epoch_37_accuracy_0.6567.pth +3 -0
- seed-222/uasyaxra-s222_resnet50/model_epoch_38_accuracy_0.6582.pth +3 -0
- seed-222/uasyaxra-s222_resnet50/model_epoch_38_f1_0.6243.pth +3 -0
- seed-222/uasyaxra-s222_resnet50/test_results.json +269 -0
seed-222/uasyaxra-s222_resnet50/metadata.yml
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args:
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best_checkpoint_metrics:
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- accuracy
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- f1
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checkpoints_dir: ./checkpoints
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dataset_dir: data/seed-222/ICH-17-processed-3-seed-222
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eval_batch_size: 64
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from_checkpoint: null
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gradient_accum_steps: 2
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label_smoothing: 0.1
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lr: 0.0001
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max_grad_norm: 1.0
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min_lr: 0.0
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mixed_precision: fp16
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model: resnet50
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model_ema_decay: 0.9999
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model_ema_warmup: false
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num_epochs: 50
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num_workers: 8
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run_test_only: false
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save_best_k: 5
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scheduler_T_0: 10
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scheduler_T_mult: 3
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seed: 222
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train_batch_size: 64
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use_ema: false
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use_mixup_cutmix: true
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wandb_logging: true
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wandb_name: s222_resnet50
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wandb_notes: null
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wandb_project: soups
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wandb_resume_id: null
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wandb_tags: null
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weight_decay: 0.001
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wandb:
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id: uasyaxra
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name: s222_resnet50
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notes: null
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project: soups
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tags: !!python/tuple []
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seed-222/uasyaxra-s222_resnet50/model_epoch_30_f1_0.6243.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:cc935c03341628bf5acad415ce4cd95a7ed0b2a15ba1cdeaba4a6316c715938c
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size 94495461
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seed-222/uasyaxra-s222_resnet50/model_epoch_31_accuracy_0.6612.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:0c0f32343dafa76f13c584ca1655536ff8a8cc78de0c90c6e5d2611fe46097df
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size 94497417
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seed-222/uasyaxra-s222_resnet50/model_epoch_31_f1_0.6280.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:d0716a75fd4d6ddfab851967cef3dd73b55015735ba8011a39259895e1ab70ab
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size 94495461
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seed-222/uasyaxra-s222_resnet50/model_epoch_33_accuracy_0.6582.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:af3c658100412b54b7a32a6377da5007b6c901a1b7a4eef7c7f9b1dd8a7a6775
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size 94497417
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seed-222/uasyaxra-s222_resnet50/model_epoch_33_f1_0.6251.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:e790bfc5b363c28637c3ff3c3be111425caa7be5f284c7e996a545acf0b29a85
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size 94495461
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seed-222/uasyaxra-s222_resnet50/model_epoch_35_accuracy_0.6597.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:e888794d2722c570362e363281eea040214139d9bcd90b7778e55d447c9d36f3
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size 94497417
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seed-222/uasyaxra-s222_resnet50/model_epoch_35_f1_0.6286.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:5c4e301d4ad9c19843da5a87b9ce18f7bc47a5799aa4608cb6c4b82d71807abf
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size 94495461
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seed-222/uasyaxra-s222_resnet50/model_epoch_37_accuracy_0.6567.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:ca69cb78c17b2e13876b11a541bc95829eeeeb077191d556f465faf7a2f3795b
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size 94497417
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seed-222/uasyaxra-s222_resnet50/model_epoch_38_accuracy_0.6582.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:c1dd9d187ce6f95afb0729372dce90464c75ab73d4948115732e9ec9d55645e1
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size 94497417
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seed-222/uasyaxra-s222_resnet50/model_epoch_38_f1_0.6243.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:2800c6ff1268341ce7e5d089ea8d73391e094f5d79232d58fb8bcbb10195b592
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size 94495461
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seed-222/uasyaxra-s222_resnet50/test_results.json
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{
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"./checkpoints/2025-06-14_12-31-24/model_epoch_30_f1_0.6243.pth": {
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| 3 |
+
"loss": "1.4131",
|
| 4 |
+
"accuracy": "0.6410",
|
| 5 |
+
"precision": "0.6008",
|
| 6 |
+
"recall": "0.6054",
|
| 7 |
+
"f1": "0.6007",
|
| 8 |
+
"per_class_accuracy": {
|
| 9 |
+
"1-ok": "0.8235",
|
| 10 |
+
"10-ok": "0.4054",
|
| 11 |
+
"11-ok": "0.7500",
|
| 12 |
+
"12-ok": "0.8438",
|
| 13 |
+
"13-ok": "0.6222",
|
| 14 |
+
"14-ok": "0.9333",
|
| 15 |
+
"15-ok": "0.5577",
|
| 16 |
+
"16-ok": "0.6111",
|
| 17 |
+
"17-ok": "0.9815",
|
| 18 |
+
"2-ok": "0.3333",
|
| 19 |
+
"3-ok": "0.9219",
|
| 20 |
+
"4-ok": "0.1500",
|
| 21 |
+
"5-ok": "0.6000",
|
| 22 |
+
"6-ok": "0.5319",
|
| 23 |
+
"7-ok": "0.5122",
|
| 24 |
+
"8-ok": "0.3636",
|
| 25 |
+
"9-ok": "0.3509"
|
| 26 |
+
}
|
| 27 |
+
},
|
| 28 |
+
"./checkpoints/2025-06-14_12-31-24/model_epoch_31_accuracy_0.6612.pth": {
|
| 29 |
+
"loss": "1.4311",
|
| 30 |
+
"accuracy": "0.6410",
|
| 31 |
+
"precision": "0.6112",
|
| 32 |
+
"recall": "0.6062",
|
| 33 |
+
"f1": "0.6031",
|
| 34 |
+
"per_class_accuracy": {
|
| 35 |
+
"1-ok": "0.8431",
|
| 36 |
+
"10-ok": "0.4054",
|
| 37 |
+
"11-ok": "0.7500",
|
| 38 |
+
"12-ok": "0.8281",
|
| 39 |
+
"13-ok": "0.5333",
|
| 40 |
+
"14-ok": "0.9333",
|
| 41 |
+
"15-ok": "0.5192",
|
| 42 |
+
"16-ok": "0.7222",
|
| 43 |
+
"17-ok": "0.9815",
|
| 44 |
+
"2-ok": "0.3889",
|
| 45 |
+
"3-ok": "0.8906",
|
| 46 |
+
"4-ok": "0.1250",
|
| 47 |
+
"5-ok": "0.6000",
|
| 48 |
+
"6-ok": "0.5532",
|
| 49 |
+
"7-ok": "0.4390",
|
| 50 |
+
"8-ok": "0.3182",
|
| 51 |
+
"9-ok": "0.4737"
|
| 52 |
+
}
|
| 53 |
+
},
|
| 54 |
+
"./checkpoints/2025-06-14_12-31-24/model_epoch_31_f1_0.6280.pth": {
|
| 55 |
+
"loss": "1.4311",
|
| 56 |
+
"accuracy": "0.6410",
|
| 57 |
+
"precision": "0.6112",
|
| 58 |
+
"recall": "0.6062",
|
| 59 |
+
"f1": "0.6031",
|
| 60 |
+
"per_class_accuracy": {
|
| 61 |
+
"1-ok": "0.8431",
|
| 62 |
+
"10-ok": "0.4054",
|
| 63 |
+
"11-ok": "0.7500",
|
| 64 |
+
"12-ok": "0.8281",
|
| 65 |
+
"13-ok": "0.5333",
|
| 66 |
+
"14-ok": "0.9333",
|
| 67 |
+
"15-ok": "0.5192",
|
| 68 |
+
"16-ok": "0.7222",
|
| 69 |
+
"17-ok": "0.9815",
|
| 70 |
+
"2-ok": "0.3889",
|
| 71 |
+
"3-ok": "0.8906",
|
| 72 |
+
"4-ok": "0.1250",
|
| 73 |
+
"5-ok": "0.6000",
|
| 74 |
+
"6-ok": "0.5532",
|
| 75 |
+
"7-ok": "0.4390",
|
| 76 |
+
"8-ok": "0.3182",
|
| 77 |
+
"9-ok": "0.4737"
|
| 78 |
+
}
|
| 79 |
+
},
|
| 80 |
+
"./checkpoints/2025-06-14_12-31-24/model_epoch_33_accuracy_0.6582.pth": {
|
| 81 |
+
"loss": "1.4230",
|
| 82 |
+
"accuracy": "0.6329",
|
| 83 |
+
"precision": "0.5987",
|
| 84 |
+
"recall": "0.5973",
|
| 85 |
+
"f1": "0.5946",
|
| 86 |
+
"per_class_accuracy": {
|
| 87 |
+
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