add s222_swin.ms_in22k_ft_in1k_drop_5
Browse files- seed-222/ovg3y4xw-s222_swin.ms_in22k_ft_in1k_drop_5/metadata.yml +40 -0
- seed-222/ovg3y4xw-s222_swin.ms_in22k_ft_in1k_drop_5/model_epoch_13_accuracy_0.7233.pth +3 -0
- seed-222/ovg3y4xw-s222_swin.ms_in22k_ft_in1k_drop_5/model_epoch_29_accuracy_0.7296.pth +3 -0
- seed-222/ovg3y4xw-s222_swin.ms_in22k_ft_in1k_drop_5/model_epoch_29_f1_0.7107.pth +3 -0
- seed-222/ovg3y4xw-s222_swin.ms_in22k_ft_in1k_drop_5/model_epoch_34_accuracy_0.7233.pth +3 -0
- seed-222/ovg3y4xw-s222_swin.ms_in22k_ft_in1k_drop_5/model_epoch_34_f1_0.7005.pth +3 -0
- seed-222/ovg3y4xw-s222_swin.ms_in22k_ft_in1k_drop_5/model_epoch_35_accuracy_0.7248.pth +3 -0
- seed-222/ovg3y4xw-s222_swin.ms_in22k_ft_in1k_drop_5/model_epoch_35_f1_0.7005.pth +3 -0
- seed-222/ovg3y4xw-s222_swin.ms_in22k_ft_in1k_drop_5/model_epoch_36_accuracy_0.7233.pth +3 -0
- seed-222/ovg3y4xw-s222_swin.ms_in22k_ft_in1k_drop_5/model_epoch_40_f1_0.6995.pth +3 -0
- seed-222/ovg3y4xw-s222_swin.ms_in22k_ft_in1k_drop_5/model_epoch_47_f1_0.7009.pth +3 -0
- seed-222/ovg3y4xw-s222_swin.ms_in22k_ft_in1k_drop_5/test_results.json +269 -0
seed-222/ovg3y4xw-s222_swin.ms_in22k_ft_in1k_drop_5/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-drop-5
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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: timm/swin_base_patch4_window7_224.ms_in22k_ft_in1k
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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: 16
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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_swin.ms_in22k_ft_in1k_drop_5
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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: ovg3y4xw
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name: s222_swin.ms_in22k_ft_in1k_drop_5
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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/ovg3y4xw-s222_swin.ms_in22k_ft_in1k_drop_5/model_epoch_13_accuracy_0.7233.pth
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version https://git-lfs.github.com/spec/v1
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size 347180166
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seed-222/ovg3y4xw-s222_swin.ms_in22k_ft_in1k_drop_5/model_epoch_29_accuracy_0.7296.pth
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size 347180166
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seed-222/ovg3y4xw-s222_swin.ms_in22k_ft_in1k_drop_5/model_epoch_29_f1_0.7107.pth
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size 347178156
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seed-222/ovg3y4xw-s222_swin.ms_in22k_ft_in1k_drop_5/model_epoch_34_accuracy_0.7233.pth
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size 347180166
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seed-222/ovg3y4xw-s222_swin.ms_in22k_ft_in1k_drop_5/model_epoch_34_f1_0.7005.pth
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size 347178156
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seed-222/ovg3y4xw-s222_swin.ms_in22k_ft_in1k_drop_5/model_epoch_35_accuracy_0.7248.pth
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size 347180166
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seed-222/ovg3y4xw-s222_swin.ms_in22k_ft_in1k_drop_5/model_epoch_35_f1_0.7005.pth
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size 347178156
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seed-222/ovg3y4xw-s222_swin.ms_in22k_ft_in1k_drop_5/model_epoch_36_accuracy_0.7233.pth
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size 347180166
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seed-222/ovg3y4xw-s222_swin.ms_in22k_ft_in1k_drop_5/model_epoch_40_f1_0.6995.pth
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size 347178156
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seed-222/ovg3y4xw-s222_swin.ms_in22k_ft_in1k_drop_5/model_epoch_47_f1_0.7009.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:9f8c8d7692f4caef76100c28a897f60b44fc54408a3ef87223424697b8f2511f
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size 347178156
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seed-222/ovg3y4xw-s222_swin.ms_in22k_ft_in1k_drop_5/test_results.json
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{
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| 2 |
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"./checkpoints/2025-06-14_13-57-48/model_epoch_47_f1_0.7009.pth": {
|
| 3 |
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"loss": "1.2739",
|
| 4 |
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"accuracy": "0.6601",
|
| 5 |
+
"precision": "0.6422",
|
| 6 |
+
"recall": "0.6248",
|
| 7 |
+
"f1": "0.6289",
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| 8 |
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"per_class_accuracy": {
|
| 9 |
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"1-ok": "0.7347",
|
| 10 |
+
"10-ok": "0.5143",
|
| 11 |
+
"11-ok": "0.7143",
|
| 12 |
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"12-ok": "0.7742",
|
| 13 |
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"13-ok": "0.5238",
|
| 14 |
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"14-ok": "0.9091",
|
| 15 |
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"15-ok": "0.6200",
|
| 16 |
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"16-ok": "0.6667",
|
| 17 |
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"17-ok": "1.0000",
|
| 18 |
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"2-ok": "0.3889",
|
| 19 |
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"3-ok": "0.9516",
|
| 20 |
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"4-ok": "0.1622",
|
| 21 |
+
"5-ok": "0.5429",
|
| 22 |
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"6-ok": "0.6818",
|
| 23 |
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"7-ok": "0.5000",
|
| 24 |
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"8-ok": "0.4286",
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| 25 |
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"9-ok": "0.5091"
|
| 26 |
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}
|
| 27 |
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},
|
| 28 |
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"./checkpoints/2025-06-14_13-57-48/model_epoch_13_accuracy_0.7233.pth": {
|
| 29 |
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"loss": "1.1667",
|
| 30 |
+
"accuracy": "0.6573",
|
| 31 |
+
"precision": "0.6123",
|
| 32 |
+
"recall": "0.6069",
|
| 33 |
+
"f1": "0.6034",
|
| 34 |
+
"per_class_accuracy": {
|
| 35 |
+
"1-ok": "0.8776",
|
| 36 |
+
"10-ok": "0.4571",
|
| 37 |
+
"11-ok": "0.7143",
|
| 38 |
+
"12-ok": "0.7903",
|
| 39 |
+
"13-ok": "0.5714",
|
| 40 |
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"14-ok": "0.9773",
|
| 41 |
+
"15-ok": "0.6600",
|
| 42 |
+
"16-ok": "0.6389",
|
| 43 |
+
"17-ok": "1.0000",
|
| 44 |
+
"2-ok": "0.2222",
|
| 45 |
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"3-ok": "0.9355",
|
| 46 |
+
"4-ok": "0.1351",
|
| 47 |
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"5-ok": "0.6286",
|
| 48 |
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"6-ok": "0.6818",
|
| 49 |
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"7-ok": "0.5500",
|
| 50 |
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"8-ok": "0.0952",
|
| 51 |
+
"9-ok": "0.3818"
|
| 52 |
+
}
|
| 53 |
+
},
|
| 54 |
+
"./checkpoints/2025-06-14_13-57-48/model_epoch_29_accuracy_0.7296.pth": {
|
| 55 |
+
"loss": "1.1932",
|
| 56 |
+
"accuracy": "0.6784",
|
| 57 |
+
"precision": "0.6578",
|
| 58 |
+
"recall": "0.6479",
|
| 59 |
+
"f1": "0.6499",
|
| 60 |
+
"per_class_accuracy": {
|
| 61 |
+
"1-ok": "0.8980",
|
| 62 |
+
"10-ok": "0.5714",
|
| 63 |
+
"11-ok": "0.7857",
|
| 64 |
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"12-ok": "0.7903",
|
| 65 |
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"13-ok": "0.5238",
|
| 66 |
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"14-ok": "0.9545",
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