Hugging Face's logo

selvaa
/
segformer-b1-finetuned-cityscapes-1024-1024-straighter-only-test

Transformers
TensorBoard
Safetensors
segformer
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
selvaa commited on
Commit
ffd6377
•
1 Parent(s): 68e8414

End of training

Browse files
Files changed (6) hide show
  1. README.md +119 -0
  2. config.json +82 -0
  3. model.safetensors +3 -0
  4. runs/Apr26_15-40-39_antd/events.out.tfevents.1714138852.antd.14323.0 +3 -0
  5. runs/Apr26_15-47-08_antd/events.out.tfevents.1714139240.antd.14626.0 +3 -0
  6. training_args.bin +3 -0
README.md ADDED
@@ -0,0 +1,119 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: other
3
+ base_model: nvidia/segformer-b1-finetuned-cityscapes-1024-1024
4
+ tags:
5
+ - vision
6
+ - image-segmentation
7
+ - generated_from_trainer
8
+ model-index:
9
+ - name: segformer-b1-finetuned-cityscapes-1024-1024-straighter-only-test
10
+ results: []
11
+ ---
12
+
13
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
14
+ should probably proofread and complete it, then remove this comment. -->
15
+
16
+ # segformer-b1-finetuned-cityscapes-1024-1024-straighter-only-test
17
+
18
+ This model is a fine-tuned version of [nvidia/segformer-b1-finetuned-cityscapes-1024-1024](https://huggingface.co/nvidia/segformer-b1-finetuned-cityscapes-1024-1024) on the selvaa/straighter-only-final dataset.
19
+ It achieves the following results on the evaluation set:
20
+ - Loss: 0.0319
21
+ - Mean Iou: 0.9378
22
+ - Mean Accuracy: 0.9615
23
+ - Overall Accuracy: 0.9895
24
+ - Accuracy Default: 1e-06
25
+ - Accuracy Pipe: 0.8987
26
+ - Accuracy Floor: 0.9897
27
+ - Accuracy Background: 0.9959
28
+ - Iou Default: 1e-06
29
+ - Iou Pipe: 0.8434
30
+ - Iou Floor: 0.9813
31
+ - Iou Background: 0.9889
32
+
33
+ ## Model description
34
+
35
+ More information needed
36
+
37
+ ## Intended uses & limitations
38
+
39
+ More information needed
40
+
41
+ ## Training and evaluation data
42
+
43
+ More information needed
44
+
45
+ ## Training procedure
46
+
47
+ ### Training hyperparameters
48
+
49
+ The following hyperparameters were used during training:
50
+ - learning_rate: 0.0002
51
+ - train_batch_size: 3
52
+ - eval_batch_size: 3
53
+ - seed: 42
54
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
55
+ - lr_scheduler_type: linear
56
+ - num_epochs: 60
57
+ - mixed_precision_training: Native AMP
58
+
59
+ ### Training results
60
+
61
+ | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Default | Accuracy Pipe | Accuracy Floor | Accuracy Background | Iou Default | Iou Pipe | Iou Floor | Iou Background |
62
+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:----------------:|:-------------:|:--------------:|:-------------------:|:-----------:|:--------:|:---------:|:--------------:|
63
+ | 0.3904 | 1.0 | 36 | 0.1465 | 0.8037 | 0.8484 | 0.9645 | 1e-06 | 0.5855 | 0.9696 | 0.9900 | 1e-06 | 0.5120 | 0.9355 | 0.9635 |
64
+ | 0.1244 | 2.0 | 72 | 0.0891 | 0.8640 | 0.9024 | 0.9766 | 1e-06 | 0.7371 | 0.9764 | 0.9938 | 1e-06 | 0.6565 | 0.9592 | 0.9762 |
65
+ | 0.0818 | 3.0 | 108 | 0.0669 | 0.8868 | 0.9178 | 0.9804 | 1e-06 | 0.7826 | 0.9745 | 0.9965 | 1e-06 | 0.7154 | 0.9657 | 0.9793 |
66
+ | 0.061 | 4.0 | 144 | 0.0525 | 0.9072 | 0.9407 | 0.9839 | 1e-06 | 0.8472 | 0.9801 | 0.9949 | 1e-06 | 0.7675 | 0.9711 | 0.9830 |
67
+ | 0.051 | 5.0 | 180 | 0.0470 | 0.9118 | 0.9444 | 0.9849 | 1e-06 | 0.8585 | 0.9790 | 0.9958 | 1e-06 | 0.7789 | 0.9722 | 0.9845 |
68
+ | 0.0461 | 6.0 | 216 | 0.0424 | 0.9191 | 0.9510 | 0.9861 | 1e-06 | 0.8736 | 0.9851 | 0.9944 | 1e-06 | 0.7959 | 0.9762 | 0.9851 |
69
+ | 0.0388 | 7.0 | 252 | 0.0401 | 0.9184 | 0.9443 | 0.9862 | 1e-06 | 0.8508 | 0.9862 | 0.9960 | 1e-06 | 0.7932 | 0.9769 | 0.9853 |
70
+ | 0.0348 | 8.0 | 288 | 0.0372 | 0.9244 | 0.9565 | 0.9870 | 1e-06 | 0.8894 | 0.9859 | 0.9943 | 1e-06 | 0.8104 | 0.9763 | 0.9865 |
71
+ | 0.0324 | 9.0 | 324 | 0.0362 | 0.9237 | 0.9486 | 0.9870 | 1e-06 | 0.8656 | 0.9833 | 0.9969 | 1e-06 | 0.8076 | 0.9773 | 0.9861 |
72
+ | 0.031 | 10.0 | 360 | 0.0349 | 0.9239 | 0.9520 | 0.9872 | 1e-06 | 0.8737 | 0.9870 | 0.9954 | 1e-06 | 0.8067 | 0.9788 | 0.9863 |
73
+ | 0.0287 | 11.0 | 396 | 0.0333 | 0.9285 | 0.9531 | 0.9877 | 1e-06 | 0.8720 | 0.9930 | 0.9944 | 1e-06 | 0.8209 | 0.9778 | 0.9868 |
74
+ | 0.0268 | 12.0 | 432 | 0.0332 | 0.9283 | 0.9522 | 0.9879 | 1e-06 | 0.8737 | 0.9865 | 0.9966 | 1e-06 | 0.8191 | 0.9787 | 0.9872 |
75
+ | 0.025 | 13.0 | 468 | 0.0311 | 0.9317 | 0.9622 | 0.9883 | 1e-06 | 0.9042 | 0.9877 | 0.9945 | 1e-06 | 0.8281 | 0.9794 | 0.9877 |
76
+ | 0.0247 | 14.0 | 504 | 0.0310 | 0.9308 | 0.9535 | 0.9884 | 1e-06 | 0.8742 | 0.9904 | 0.9959 | 1e-06 | 0.8247 | 0.9801 | 0.9876 |
77
+ | 0.0236 | 15.0 | 540 | 0.0307 | 0.9322 | 0.9538 | 0.9886 | 1e-06 | 0.8755 | 0.9897 | 0.9963 | 1e-06 | 0.8292 | 0.9793 | 0.9880 |
78
+ | 0.0223 | 16.0 | 576 | 0.0301 | 0.9346 | 0.9633 | 0.9888 | 1e-06 | 0.9083 | 0.9861 | 0.9955 | 1e-06 | 0.8360 | 0.9791 | 0.9886 |
79
+ | 0.0208 | 17.0 | 612 | 0.0308 | 0.9326 | 0.9578 | 0.9887 | 1e-06 | 0.8876 | 0.9907 | 0.9953 | 1e-06 | 0.8300 | 0.9797 | 0.9882 |
80
+ | 0.0198 | 18.0 | 648 | 0.0295 | 0.9339 | 0.9589 | 0.9888 | 1e-06 | 0.8897 | 0.9921 | 0.9949 | 1e-06 | 0.8335 | 0.9799 | 0.9882 |
81
+ | 0.0194 | 19.0 | 684 | 0.0311 | 0.9315 | 0.9524 | 0.9886 | 1e-06 | 0.8712 | 0.9894 | 0.9967 | 1e-06 | 0.8265 | 0.9802 | 0.9878 |
82
+ | 0.0188 | 20.0 | 720 | 0.0299 | 0.9332 | 0.9558 | 0.9888 | 1e-06 | 0.8807 | 0.9906 | 0.9959 | 1e-06 | 0.8318 | 0.9796 | 0.9882 |
83
+ | 0.0187 | 21.0 | 756 | 0.0298 | 0.9344 | 0.9567 | 0.9890 | 1e-06 | 0.8833 | 0.9905 | 0.9961 | 1e-06 | 0.8339 | 0.9810 | 0.9883 |
84
+ | 0.0179 | 22.0 | 792 | 0.0304 | 0.9334 | 0.9566 | 0.9889 | 1e-06 | 0.8834 | 0.9904 | 0.9959 | 1e-06 | 0.8317 | 0.9804 | 0.9882 |
85
+ | 0.0174 | 23.0 | 828 | 0.0301 | 0.9350 | 0.9603 | 0.9890 | 1e-06 | 0.8960 | 0.9895 | 0.9955 | 1e-06 | 0.8364 | 0.9803 | 0.9884 |
86
+ | 0.017 | 24.0 | 864 | 0.0294 | 0.9352 | 0.9589 | 0.9890 | 1e-06 | 0.8925 | 0.9877 | 0.9963 | 1e-06 | 0.8371 | 0.9802 | 0.9883 |
87
+ | 0.0172 | 25.0 | 900 | 0.0322 | 0.9334 | 0.9555 | 0.9888 | 1e-06 | 0.8796 | 0.9908 | 0.9960 | 1e-06 | 0.8320 | 0.9799 | 0.9882 |
88
+ | 0.0165 | 26.0 | 936 | 0.0312 | 0.9331 | 0.9556 | 0.9888 | 1e-06 | 0.8813 | 0.9891 | 0.9964 | 1e-06 | 0.8318 | 0.9792 | 0.9884 |
89
+ | 0.0162 | 27.0 | 972 | 0.0296 | 0.9350 | 0.9589 | 0.9891 | 1e-06 | 0.8911 | 0.9899 | 0.9959 | 1e-06 | 0.8360 | 0.9806 | 0.9885 |
90
+ | 0.0155 | 28.0 | 1008 | 0.0314 | 0.9359 | 0.9578 | 0.9892 | 1e-06 | 0.8880 | 0.9890 | 0.9965 | 1e-06 | 0.8384 | 0.9808 | 0.9884 |
91
+ | 0.0154 | 29.0 | 1044 | 0.0291 | 0.9379 | 0.9637 | 0.9894 | 1e-06 | 0.9061 | 0.9898 | 0.9952 | 1e-06 | 0.8438 | 0.9812 | 0.9887 |
92
+ | 0.0151 | 30.0 | 1080 | 0.0289 | 0.9372 | 0.9620 | 0.9893 | 1e-06 | 0.8994 | 0.9912 | 0.9952 | 1e-06 | 0.8419 | 0.9810 | 0.9887 |
93
+ | 0.0152 | 31.0 | 1116 | 0.0310 | 0.9365 | 0.9573 | 0.9893 | 1e-06 | 0.8865 | 0.9884 | 0.9969 | 1e-06 | 0.8397 | 0.9815 | 0.9884 |
94
+ | 0.0143 | 32.0 | 1152 | 0.0307 | 0.9376 | 0.9614 | 0.9894 | 1e-06 | 0.8983 | 0.9904 | 0.9956 | 1e-06 | 0.8433 | 0.9809 | 0.9887 |
95
+ | 0.0138 | 33.0 | 1188 | 0.0295 | 0.9385 | 0.9623 | 0.9896 | 1e-06 | 0.9004 | 0.9910 | 0.9955 | 1e-06 | 0.8451 | 0.9814 | 0.9889 |
96
+ | 0.0149 | 34.0 | 1224 | 0.0308 | 0.9380 | 0.9617 | 0.9894 | 1e-06 | 0.9007 | 0.9883 | 0.9961 | 1e-06 | 0.8444 | 0.9809 | 0.9886 |
97
+ | 0.0138 | 35.0 | 1260 | 0.0304 | 0.9376 | 0.9616 | 0.9894 | 1e-06 | 0.8993 | 0.9899 | 0.9958 | 1e-06 | 0.8431 | 0.9809 | 0.9888 |
98
+ | 0.0138 | 36.0 | 1296 | 0.0299 | 0.9379 | 0.9598 | 0.9895 | 1e-06 | 0.8932 | 0.9901 | 0.9962 | 1e-06 | 0.8433 | 0.9816 | 0.9887 |
99
+ | 0.0139 | 37.0 | 1332 | 0.0298 | 0.9378 | 0.9615 | 0.9895 | 1e-06 | 0.8983 | 0.9903 | 0.9958 | 1e-06 | 0.8435 | 0.9812 | 0.9889 |
100
+ | 0.0133 | 38.0 | 1368 | 0.0293 | 0.9393 | 0.9624 | 0.9897 | 1e-06 | 0.9008 | 0.9906 | 0.9958 | 1e-06 | 0.8467 | 0.9823 | 0.9889 |
101
+ | 0.0131 | 39.0 | 1404 | 0.0318 | 0.9368 | 0.9592 | 0.9893 | 1e-06 | 0.8922 | 0.9893 | 0.9963 | 1e-06 | 0.8406 | 0.9814 | 0.9884 |
102
+ | 0.0129 | 40.0 | 1440 | 0.0303 | 0.9382 | 0.9627 | 0.9895 | 1e-06 | 0.9034 | 0.9890 | 0.9958 | 1e-06 | 0.8447 | 0.9813 | 0.9887 |
103
+ | 0.0126 | 41.0 | 1476 | 0.0304 | 0.9392 | 0.9631 | 0.9896 | 1e-06 | 0.9037 | 0.9901 | 0.9956 | 1e-06 | 0.8471 | 0.9818 | 0.9887 |
104
+ | 0.0126 | 42.0 | 1512 | 0.0311 | 0.9378 | 0.9595 | 0.9895 | 1e-06 | 0.8929 | 0.9892 | 0.9965 | 1e-06 | 0.8432 | 0.9817 | 0.9887 |
105
+ | 0.0125 | 43.0 | 1548 | 0.0314 | 0.9383 | 0.9611 | 0.9895 | 1e-06 | 0.8974 | 0.9899 | 0.9960 | 1e-06 | 0.8453 | 0.9809 | 0.9888 |
106
+ | 0.0129 | 44.0 | 1584 | 0.0319 | 0.9374 | 0.9585 | 0.9895 | 1e-06 | 0.8886 | 0.9904 | 0.9964 | 1e-06 | 0.8420 | 0.9816 | 0.9887 |
107
+ | 0.0127 | 45.0 | 1620 | 0.0313 | 0.9380 | 0.9594 | 0.9895 | 1e-06 | 0.8920 | 0.9900 | 0.9964 | 1e-06 | 0.8436 | 0.9816 | 0.9887 |
108
+ | 0.0127 | 46.0 | 1656 | 0.0321 | 0.9379 | 0.9626 | 0.9895 | 1e-06 | 0.9029 | 0.9893 | 0.9957 | 1e-06 | 0.8444 | 0.9805 | 0.9890 |
109
+ | 0.0121 | 47.0 | 1692 | 0.0321 | 0.9377 | 0.9599 | 0.9895 | 1e-06 | 0.8930 | 0.9907 | 0.9960 | 1e-06 | 0.8430 | 0.9813 | 0.9888 |
110
+ | 0.0115 | 48.0 | 1728 | 0.0305 | 0.9390 | 0.9633 | 0.9897 | 1e-06 | 0.9043 | 0.9900 | 0.9957 | 1e-06 | 0.8463 | 0.9817 | 0.9890 |
111
+ | 0.0118 | 49.0 | 1764 | 0.0319 | 0.9378 | 0.9615 | 0.9895 | 1e-06 | 0.8987 | 0.9897 | 0.9959 | 1e-06 | 0.8434 | 0.9813 | 0.9889 |
112
+
113
+
114
+ ### Framework versions
115
+
116
+ - Transformers 4.35.2
117
+ - Pytorch 2.0.1
118
+ - Datasets 2.15.0
119
+ - Tokenizers 0.15.0
config.json ADDED
@@ -0,0 +1,82 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "nvidia/segformer-b1-finetuned-cityscapes-1024-1024",
3
+ "architectures": [
4
+ "SegformerForSemanticSegmentation"
5
+ ],
6
+ "attention_probs_dropout_prob": 0.0,
7
+ "classifier_dropout_prob": 0.1,
8
+ "decoder_hidden_size": 256,
9
+ "depths": [
10
+ 2,
11
+ 2,
12
+ 2,
13
+ 2
14
+ ],
15
+ "downsampling_rates": [
16
+ 1,
17
+ 4,
18
+ 8,
19
+ 16
20
+ ],
21
+ "drop_path_rate": 0.1,
22
+ "hidden_act": "gelu",
23
+ "hidden_dropout_prob": 0.0,
24
+ "hidden_sizes": [
25
+ 64,
26
+ 128,
27
+ 320,
28
+ 512
29
+ ],
30
+ "id2label": {
31
+ "0": "default",
32
+ "1": "pipe",
33
+ "2": "floor",
34
+ "3": "background"
35
+ },
36
+ "image_size": 224,
37
+ "initializer_range": 0.02,
38
+ "label2id": {
39
+ "background": 3,
40
+ "default": 0,
41
+ "floor": 2,
42
+ "pipe": 1
43
+ },
44
+ "layer_norm_eps": 1e-06,
45
+ "mlp_ratios": [
46
+ 4,
47
+ 4,
48
+ 4,
49
+ 4
50
+ ],
51
+ "model_type": "segformer",
52
+ "num_attention_heads": [
53
+ 1,
54
+ 2,
55
+ 5,
56
+ 8
57
+ ],
58
+ "num_channels": 3,
59
+ "num_encoder_blocks": 4,
60
+ "patch_sizes": [
61
+ 7,
62
+ 3,
63
+ 3,
64
+ 3
65
+ ],
66
+ "reshape_last_stage": true,
67
+ "semantic_loss_ignore_index": 255,
68
+ "sr_ratios": [
69
+ 8,
70
+ 4,
71
+ 2,
72
+ 1
73
+ ],
74
+ "strides": [
75
+ 4,
76
+ 2,
77
+ 2,
78
+ 2
79
+ ],
80
+ "torch_dtype": "float32",
81
+ "transformers_version": "4.35.2"
82
+ }
model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:2863ea8786c0f6e877c33d6490331276054cb0b146e87162d52d8e337e0008df
3
+ size 54739432
runs/Apr26_15-40-39_antd/events.out.tfevents.1714138852.antd.14323.0 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7c9a1206557956e86215729bd13a5da5b8784465d0d0ffe0f5fa0da18c7f7243
3
+ size 4993
runs/Apr26_15-47-08_antd/events.out.tfevents.1714139240.antd.14626.0 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5f96d370197ccea651b227c37dd4f48a542a907309ff34cf3c1a8bcaa8e41834
3
+ size 56887
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e0b30ea4f29835ac1bf41e7ea817e8a16a4e68c063f5f754cf5c3b32f0087dd4
3
+ size 4347