training 20 epochs

dvc.lock

@@ -8,18 +8,21 @@ stages:
  size: 28867246
  nfiles: 1482
  - path: params.yaml
- md5: 54726043d2a91378df53a641d25d5dac
- size: 215
+ md5: a061a8a3138da65df56595927ca325f6
+ size: 216
  - path: src/train.py
  md5: 8cde4fe436744929ddbaeaadb37aad71
  size: 986
+ - path: src/utils.py
+ md5: 3ecd480350d0d8edb7e4ba533bb555ad
+ size: 1253
  outs:
  - path: models/model.pt
- md5: 63fce0b37345cecfc51b75a871d46560
+ md5: 31c95b64b4a92e32e26ca67d99ffc401
  size: 22495096
  - path: reports/train_metrics.csv
- md5: d3ee99e7a651b8b69535c7dcff8ea64d
- size: 672
+ md5: 30cf68a8a216e4dcfbde8717fa882e9f
+ size: 7056
  - path: reports/train_params.yaml
- md5: a13c7b98780812835f127700894323c7
- size: 1501
+ md5: 5c58f717d9f2b23de0e7483ba7fbf2b2
+ size: 1502

dvc.yaml

@@ -4,7 +4,7 @@ stages:
  deps:
  - data/raw/wildfire-raw-yolov8
  - src/train.py
- params:
+ - src/utils.py
  - params.yaml
  outs:
  - models/model.pt

params.yaml

@@ -3,7 +3,7 @@ pretrained: True
 seed: 0
 imgsz: 640 
 batch: 8 
-epochs: 1
+epochs: 20
 optimizer: SGD # other choices=['SGD', 'Adam', 'AdamW', 'RMSProp']
 lr0: 0.01 # learning rate 
 name: 'yolov8s_exp_v0' # experiment name

reports/train_metrics.csv

@@ -1,2 +1,21 @@
  epoch, train/box_loss, train/cls_loss, train/dfl_loss, metrics/precision(B), metrics/recall(B), metrics/mAP50(B), metrics/mAP50-95(B), val/box_loss, val/cls_loss, val/dfl_loss, lr/pg0, lr/pg1, lr/pg2
  0, 2.074, 3.6688, 1.7378, 0.29774, 0.32591, 0.23183, 0.08104, 2.2504, 2.6345, 1.8202, 0.070462, 0.0032821, 0.0032821
+ 1, 1.767, 1.7208, 1.4953, 0.64651, 0.53061, 0.62556, 0.29666, 1.8773, 1.8427, 1.3876, 0.040134, 0.0062879, 0.0062879
+ 2, 1.7171, 1.707, 1.3988, 0.06729, 0.09524, 0.04705, 0.02481, 3.0641, 4.3916, 2.5411, 0.0094766, 0.0089638, 0.0089638
+ 3, 1.7341, 1.8335, 1.4552, 0.38806, 0.47619, 0.41508, 0.17576, 1.9845, 2.1096, 1.6549, 0.008515, 0.008515, 0.008515
+ 4, 1.691, 1.3376, 1.4286, 0.49323, 0.42177, 0.41415, 0.16903, 2.213, 2.0351, 1.7182, 0.008515, 0.008515, 0.008515
+ 5, 1.6586, 1.3538, 1.3919, 0.62787, 0.38095, 0.39228, 0.18293, 2.0223, 2.3359, 1.6252, 0.00802, 0.00802, 0.00802
+ 6, 1.6037, 1.2676, 1.3543, 0.66557, 0.47619, 0.5516, 0.25586, 1.8962, 1.6098, 1.4971, 0.007525, 0.007525, 0.007525
+ 7, 1.658, 1.2554, 1.3514, 0.58698, 0.68027, 0.6487, 0.29438, 1.7871, 1.3586, 1.4083, 0.00703, 0.00703, 0.00703
+ 8, 1.609, 1.1162, 1.3305, 0.6504, 0.5102, 0.53742, 0.25941, 1.9, 1.6061, 1.4134, 0.006535, 0.006535, 0.006535
+ 9, 1.5784, 1.1193, 1.3391, 0.58894, 0.70068, 0.60387, 0.26491, 1.8898, 1.466, 1.4003, 0.00604, 0.00604, 0.00604
+ 10, 1.6081, 1.0872, 1.332, 0.54884, 0.53741, 0.56067, 0.26937, 1.89, 1.6558, 1.4405, 0.005545, 0.005545, 0.005545
+ 11, 1.6216, 1.0673, 1.3576, 0.6775, 0.7415, 0.76254, 0.40175, 1.6952, 1.1328, 1.3126, 0.00505, 0.00505, 0.00505
+ 12, 1.5426, 1.0814, 1.3183, 0.63694, 0.73995, 0.67857, 0.33739, 1.8035, 1.2909, 1.3621, 0.004555, 0.004555, 0.004555
+ 13, 1.527, 0.9778, 1.2827, 0.76852, 0.76871, 0.80068, 0.40906, 1.6945, 1.0812, 1.3067, 0.00406, 0.00406, 0.00406
+ 14, 1.4765, 0.93611, 1.2862, 0.74653, 0.84152, 0.85997, 0.47623, 1.6398, 1.0427, 1.3348, 0.003565, 0.003565, 0.003565
+ 15, 1.4623, 0.90297, 1.2588, 0.83993, 0.80952, 0.88026, 0.47516, 1.6723, 0.98866, 1.2993, 0.00307, 0.00307, 0.00307
+ 16, 1.4283, 0.86243, 1.2558, 0.81461, 0.82313, 0.90594, 0.46365, 1.6496, 0.93395, 1.3134, 0.002575, 0.002575, 0.002575
+ 17, 1.4264, 0.83566, 1.2381, 0.85204, 0.82993, 0.90175, 0.49576, 1.5633, 0.94734, 1.2569, 0.00208, 0.00208, 0.00208
+ 18, 1.3657, 0.84115, 1.214, 0.87301, 0.87755, 0.922, 0.4962, 1.5714, 0.88971, 1.2903, 0.001585, 0.001585, 0.001585
+ 19, 1.3289, 0.8171, 1.1956, 0.85437, 0.86395, 0.92797, 0.51129, 1.5971, 0.85184, 1.2837, 0.00109, 0.00109, 0.00109

reports/train_params.yaml

@@ -2,7 +2,7 @@ task: detect
 mode: train
 model: yolov8s.pt
 data: /Users/rihabfeki/Desktop/wildfire-smoke-detector/data/raw/wildfire-raw-yolov8/data.yaml
-epochs: 1
+epochs: 20
 patience: 50
 batch: 8
 imgsz: 640