Hugging Face's logo

peldrak
/
segformer-b5-ade-finetuned-coastTrain

Image Segmentation
Transformers
TensorBoard
Safetensors
segformer
vision
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
peldrak commited on
Commit
07ab89d
•
1 Parent(s): d167a6f

End of training

Browse files
Files changed (5) hide show
  1. README.md +129 -198
  2. config.json +88 -0
  3. model.safetensors +3 -0
  4. runs/Mar06_14-50-05_c8ef0f2261eb/events.out.tfevents.1709736608.c8ef0f2261eb.26.0 +3 -0
  5. training_args.bin +3 -0
README.md CHANGED
@@ -1,201 +1,132 @@
1
  ---
2
- library_name: transformers
3
- tags: []
 
 
 
 
 
 
 
4
  ---
5
 
6
- # Model Card for Model ID
7
-
8
- <!-- Provide a quick summary of what the model is/does. -->
9
-
10
-
11
-
12
- ## Model Details
13
-
14
- ### Model Description
15
-
16
- <!-- Provide a longer summary of what this model is. -->
17
-
18
- This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
19
-
20
- - **Developed by:** [More Information Needed]
21
- - **Funded by [optional]:** [More Information Needed]
22
- - **Shared by [optional]:** [More Information Needed]
23
- - **Model type:** [More Information Needed]
24
- - **Language(s) (NLP):** [More Information Needed]
25
- - **License:** [More Information Needed]
26
- - **Finetuned from model [optional]:** [More Information Needed]
27
-
28
- ### Model Sources [optional]
29
-
30
- <!-- Provide the basic links for the model. -->
31
-
32
- - **Repository:** [More Information Needed]
33
- - **Paper [optional]:** [More Information Needed]
34
- - **Demo [optional]:** [More Information Needed]
35
-
36
- ## Uses
37
-
38
- <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
-
40
- ### Direct Use
41
-
42
- <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
-
44
- [More Information Needed]
45
-
46
- ### Downstream Use [optional]
47
-
48
- <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
-
50
- [More Information Needed]
51
-
52
- ### Out-of-Scope Use
53
-
54
- <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
-
56
- [More Information Needed]
57
-
58
- ## Bias, Risks, and Limitations
59
-
60
- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
-
62
- [More Information Needed]
63
-
64
- ### Recommendations
65
-
66
- <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
-
68
- Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
-
70
- ## How to Get Started with the Model
71
-
72
- Use the code below to get started with the model.
73
-
74
- [More Information Needed]
75
-
76
- ## Training Details
77
-
78
- ### Training Data
79
-
80
- <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
-
82
- [More Information Needed]
83
-
84
- ### Training Procedure
85
-
86
- <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
-
88
- #### Preprocessing [optional]
89
-
90
- [More Information Needed]
91
-
92
-
93
- #### Training Hyperparameters
94
-
95
- - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
-
97
- #### Speeds, Sizes, Times [optional]
98
-
99
- <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
-
101
- [More Information Needed]
102
-
103
- ## Evaluation
104
-
105
- <!-- This section describes the evaluation protocols and provides the results. -->
106
-
107
- ### Testing Data, Factors & Metrics
108
-
109
- #### Testing Data
110
-
111
- <!-- This should link to a Dataset Card if possible. -->
112
-
113
- [More Information Needed]
114
-
115
- #### Factors
116
-
117
- <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
-
119
- [More Information Needed]
120
-
121
- #### Metrics
122
-
123
- <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
-
125
- [More Information Needed]
126
-
127
- ### Results
128
-
129
- [More Information Needed]
130
-
131
- #### Summary
132
-
133
-
134
-
135
- ## Model Examination [optional]
136
-
137
- <!-- Relevant interpretability work for the model goes here -->
138
-
139
- [More Information Needed]
140
-
141
- ## Environmental Impact
142
-
143
- <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
-
145
- Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
-
147
- - **Hardware Type:** [More Information Needed]
148
- - **Hours used:** [More Information Needed]
149
- - **Cloud Provider:** [More Information Needed]
150
- - **Compute Region:** [More Information Needed]
151
- - **Carbon Emitted:** [More Information Needed]
152
-
153
- ## Technical Specifications [optional]
154
-
155
- ### Model Architecture and Objective
156
-
157
- [More Information Needed]
158
-
159
- ### Compute Infrastructure
160
-
161
- [More Information Needed]
162
-
163
- #### Hardware
164
-
165
- [More Information Needed]
166
-
167
- #### Software
168
-
169
- [More Information Needed]
170
-
171
- ## Citation [optional]
172
-
173
- <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
-
175
- **BibTeX:**
176
-
177
- [More Information Needed]
178
-
179
- **APA:**
180
-
181
- [More Information Needed]
182
-
183
- ## Glossary [optional]
184
-
185
- <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
-
187
- [More Information Needed]
188
-
189
- ## More Information [optional]
190
-
191
- [More Information Needed]
192
-
193
- ## Model Card Authors [optional]
194
-
195
- [More Information Needed]
196
-
197
- ## Model Card Contact
198
-
199
- [More Information Needed]
200
-
201
-
 
1
  ---
2
+ license: other
3
+ base_model: nvidia/segformer-b5-finetuned-ade-640-640
4
+ tags:
5
+ - vision
6
+ - image-segmentation
7
+ - generated_from_trainer
8
+ model-index:
9
+ - name: segformer-b5-ade-finetuned-coastTrain
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-b5-ade-finetuned-coastTrain
17
+
18
+ This model is a fine-tuned version of [nvidia/segformer-b5-finetuned-ade-640-640](https://huggingface.co/nvidia/segformer-b5-finetuned-ade-640-640) on the peldrak/coastTrain dataset.
19
+ It achieves the following results on the evaluation set:
20
+ - Loss: 0.3412
21
+ - Mean Iou: 0.7737
22
+ - Mean Accuracy: 0.8545
23
+ - Overall Accuracy: 0.9252
24
+ - Accuracy Water: 0.9680
25
+ - Accuracy Whitewater: 0.6271
26
+ - Accuracy Sediment: 0.8745
27
+ - Accuracy Other Natural Terrain: 0.8030
28
+ - Accuracy Vegetation: 0.9108
29
+ - Accuracy Development: 0.8296
30
+ - Accuracy Unknown: 0.9682
31
+ - Iou Water: 0.9285
32
+ - Iou Whitewater: 0.5294
33
+ - Iou Sediment: 0.8047
34
+ - Iou Other Natural Terrain: 0.6748
35
+ - Iou Vegetation: 0.8430
36
+ - Iou Development: 0.7686
37
+ - Iou Unknown: 0.8673
38
+ - F1 Score: 0.9245
39
+
40
+ ## Model description
41
+
42
+ More information needed
43
+
44
+ ## Intended uses & limitations
45
+
46
+ More information needed
47
+
48
+ ## Training and evaluation data
49
+
50
+ More information needed
51
+
52
+ ## Training procedure
53
+
54
+ ### Training hyperparameters
55
+
56
+ The following hyperparameters were used during training:
57
+ - learning_rate: 6e-05
58
+ - train_batch_size: 4
59
+ - eval_batch_size: 4
60
+ - seed: 42
61
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
62
+ - lr_scheduler_type: linear
63
+ - num_epochs: 20
64
+
65
+ ### Training results
66
+
67
+ | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Water | Accuracy Whitewater | Accuracy Sediment | Accuracy Other Natural Terrain | Accuracy Vegetation | Accuracy Development | Accuracy Unknown | Iou Water | Iou Whitewater | Iou Sediment | Iou Other Natural Terrain | Iou Vegetation | Iou Development | Iou Unknown | F1 Score |
68
+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:--------------:|:-------------------:|:-----------------:|:------------------------------:|:-------------------:|:--------------------:|:----------------:|:---------:|:--------------:|:------------:|:-------------------------:|:--------------:|:---------------:|:-----------:|:--------:|
69
+ | 1.6133 | 0.16 | 20 | 1.4728 | 0.4356 | 0.5582 | 0.7600 | 0.8440 | 0.0000 | 0.5434 | 0.2624 | 0.8192 | 0.5884 | 0.8502 | 0.7387 | 0.0000 | 0.4669 | 0.1171 | 0.5786 | 0.4642 | 0.6833 | 0.7532 |
70
+ | 1.4431 | 0.31 | 40 | 1.0911 | 0.4768 | 0.5735 | 0.8206 | 0.9076 | 0.0 | 0.7765 | 0.0006 | 0.9006 | 0.6686 | 0.7608 | 0.8394 | 0.0 | 0.5832 | 0.0006 | 0.6596 | 0.4954 | 0.7597 | 0.8114 |
71
+ | 1.5275 | 0.47 | 60 | 0.7874 | 0.5222 | 0.5966 | 0.8585 | 0.9553 | 0.0 | 0.7752 | 0.0 | 0.9101 | 0.6629 | 0.8727 | 0.8565 | 0.0 | 0.6318 | 0.0 | 0.7222 | 0.5763 | 0.8688 | 0.8454 |
72
+ | 1.1583 | 0.62 | 80 | 0.7113 | 0.5128 | 0.6001 | 0.8440 | 0.8830 | 0.0 | 0.8460 | 0.0 | 0.9323 | 0.6588 | 0.8809 | 0.8283 | 0.0 | 0.5762 | 0.0 | 0.7216 | 0.5873 | 0.8762 | 0.8348 |
73
+ | 0.9739 | 0.78 | 100 | 0.6059 | 0.5450 | 0.6229 | 0.8733 | 0.9534 | 0.0 | 0.8246 | 0.0 | 0.8876 | 0.8146 | 0.8803 | 0.8703 | 0.0 | 0.6770 | 0.0 | 0.7506 | 0.6408 | 0.8760 | 0.8615 |
74
+ | 0.838 | 0.93 | 120 | 0.5250 | 0.5557 | 0.6273 | 0.8800 | 0.9679 | 0.0 | 0.8549 | 0.0 | 0.8665 | 0.8087 | 0.8934 | 0.8677 | 0.0 | 0.6840 | 0.0 | 0.7703 | 0.6847 | 0.8830 | 0.8674 |
75
+ | 0.5815 | 1.09 | 140 | 0.4973 | 0.5528 | 0.6247 | 0.8788 | 0.9630 | 0.0 | 0.7933 | 0.0 | 0.9010 | 0.8217 | 0.8939 | 0.8812 | 0.0 | 0.6938 | 0.0 | 0.7379 | 0.6730 | 0.8837 | 0.8663 |
76
+ | 0.5949 | 1.24 | 160 | 0.4460 | 0.5538 | 0.6314 | 0.8813 | 0.9621 | 0.0 | 0.8044 | 0.0 | 0.8840 | 0.8692 | 0.9000 | 0.8930 | 0.0 | 0.7062 | 0.0 | 0.7445 | 0.6487 | 0.8843 | 0.8695 |
77
+ | 1.089 | 1.4 | 180 | 0.4080 | 0.5666 | 0.6331 | 0.8889 | 0.9680 | 0.0 | 0.8240 | 0.0 | 0.9200 | 0.8256 | 0.8940 | 0.8902 | 0.0 | 0.7323 | 0.0 | 0.7603 | 0.6986 | 0.8846 | 0.8762 |
78
+ | 0.959 | 1.55 | 200 | 0.3853 | 0.5675 | 0.6403 | 0.8901 | 0.9611 | 0.0 | 0.8645 | 0.0 | 0.8983 | 0.8616 | 0.8964 | 0.8975 | 0.0 | 0.7192 | 0.0 | 0.7672 | 0.7035 | 0.8848 | 0.8780 |
79
+ | 0.577 | 1.71 | 220 | 0.3735 | 0.5683 | 0.6338 | 0.8902 | 0.9760 | 0.0 | 0.7882 | 0.0009 | 0.9125 | 0.8542 | 0.9047 | 0.8780 | 0.0 | 0.6862 | 0.0009 | 0.8013 | 0.7191 | 0.8927 | 0.8769 |
80
+ | 0.9331 | 1.86 | 240 | 0.3605 | 0.5705 | 0.6464 | 0.8943 | 0.9648 | 0.0 | 0.8650 | 0.0 | 0.8805 | 0.8960 | 0.9181 | 0.9010 | 0.0 | 0.7210 | 0.0 | 0.7994 | 0.6841 | 0.8879 | 0.8823 |
81
+ | 0.5132 | 2.02 | 260 | 0.3680 | 0.5826 | 0.6573 | 0.8884 | 0.9366 | 0.0 | 0.8773 | 0.1041 | 0.9113 | 0.8567 | 0.9152 | 0.8694 | 0.0 | 0.6984 | 0.1041 | 0.8038 | 0.7009 | 0.9013 | 0.8784 |
82
+ | 0.3977 | 2.17 | 280 | 0.3233 | 0.5814 | 0.6498 | 0.9018 | 0.9623 | 0.0 | 0.8900 | 0.0 | 0.9162 | 0.8487 | 0.9313 | 0.9052 | 0.0 | 0.7370 | 0.0 | 0.8210 | 0.7242 | 0.8824 | 0.8891 |
83
+ | 0.6267 | 2.33 | 300 | 0.3394 | 0.5998 | 0.6646 | 0.8980 | 0.9735 | 0.0 | 0.8603 | 0.1726 | 0.9086 | 0.8262 | 0.9110 | 0.8862 | 0.0 | 0.7533 | 0.1726 | 0.8293 | 0.7044 | 0.8531 | 0.8871 |
84
+ | 0.7394 | 2.48 | 320 | 0.3483 | 0.5776 | 0.6508 | 0.8996 | 0.9566 | 0.0 | 0.9175 | 0.0028 | 0.9041 | 0.8487 | 0.9261 | 0.9054 | 0.0 | 0.7360 | 0.0028 | 0.8317 | 0.7110 | 0.8563 | 0.8874 |
85
+ | 0.4013 | 2.64 | 340 | 0.3393 | 0.5746 | 0.6458 | 0.8987 | 0.9734 | 0.0 | 0.8959 | 0.0001 | 0.8831 | 0.8420 | 0.9264 | 0.9071 | 0.0 | 0.7357 | 0.0001 | 0.8252 | 0.7013 | 0.8525 | 0.8859 |
86
+ | 0.3434 | 2.79 | 360 | 0.3745 | 0.6263 | 0.6907 | 0.9002 | 0.9516 | 0.0003 | 0.8148 | 0.3544 | 0.9583 | 0.8127 | 0.9431 | 0.9068 | 0.0003 | 0.7490 | 0.3541 | 0.7943 | 0.7221 | 0.8576 | 0.8911 |
87
+ | 0.5902 | 2.95 | 380 | 0.3275 | 0.6068 | 0.6696 | 0.9005 | 0.9722 | 0.0 | 0.8696 | 0.1949 | 0.9158 | 0.8191 | 0.9156 | 0.8941 | 0.0 | 0.7545 | 0.1948 | 0.8224 | 0.7303 | 0.8512 | 0.8898 |
88
+ | 0.2954 | 3.1 | 400 | 0.3389 | 0.6191 | 0.6862 | 0.9008 | 0.9662 | 0.0020 | 0.8410 | 0.3092 | 0.9207 | 0.8331 | 0.9316 | 0.9074 | 0.0020 | 0.7641 | 0.3056 | 0.8117 | 0.7045 | 0.8386 | 0.8913 |
89
+ | 0.4758 | 3.26 | 420 | 0.3122 | 0.6064 | 0.6709 | 0.9030 | 0.9682 | 0.0 | 0.9069 | 0.1837 | 0.9142 | 0.7957 | 0.9279 | 0.9092 | 0.0 | 0.7655 | 0.1834 | 0.8172 | 0.7227 | 0.8466 | 0.8923 |
90
+ | 0.6415 | 3.41 | 440 | 0.3109 | 0.6555 | 0.7172 | 0.9101 | 0.9728 | 0.0017 | 0.9050 | 0.4656 | 0.8885 | 0.8320 | 0.9550 | 0.9063 | 0.0017 | 0.7957 | 0.4534 | 0.8265 | 0.7512 | 0.8539 | 0.9014 |
91
+ | 0.5413 | 3.57 | 460 | 0.2993 | 0.6420 | 0.7045 | 0.9057 | 0.9737 | 0.0036 | 0.8782 | 0.4118 | 0.8932 | 0.8221 | 0.9487 | 0.9047 | 0.0036 | 0.7774 | 0.4103 | 0.8169 | 0.7262 | 0.8553 | 0.8967 |
92
+ | 0.2761 | 3.72 | 480 | 0.2802 | 0.6678 | 0.7309 | 0.9144 | 0.9619 | 0.0191 | 0.9168 | 0.5126 | 0.9190 | 0.8330 | 0.9542 | 0.9143 | 0.0191 | 0.7850 | 0.4981 | 0.8452 | 0.7427 | 0.8699 | 0.9067 |
93
+ | 0.3451 | 3.88 | 500 | 0.3261 | 0.6455 | 0.7056 | 0.9075 | 0.9695 | 0.0220 | 0.8345 | 0.4049 | 0.9307 | 0.8256 | 0.9520 | 0.9085 | 0.0220 | 0.7754 | 0.3995 | 0.8173 | 0.7375 | 0.8583 | 0.8988 |
94
+ | 0.2361 | 4.03 | 520 | 0.3118 | 0.6677 | 0.7285 | 0.9098 | 0.9683 | 0.0204 | 0.8678 | 0.5447 | 0.9117 | 0.8323 | 0.9547 | 0.9089 | 0.0204 | 0.7750 | 0.5374 | 0.8235 | 0.7509 | 0.8580 | 0.9019 |
95
+ | 0.2776 | 4.19 | 540 | 0.2765 | 0.6472 | 0.7121 | 0.9109 | 0.9670 | 0.0359 | 0.9025 | 0.3801 | 0.9057 | 0.8431 | 0.9507 | 0.9182 | 0.0358 | 0.7698 | 0.3764 | 0.8356 | 0.7324 | 0.8619 | 0.9029 |
96
+ | 0.3823 | 4.34 | 560 | 0.3514 | 0.6558 | 0.7181 | 0.9111 | 0.9592 | 0.0525 | 0.9005 | 0.4047 | 0.9183 | 0.8321 | 0.9591 | 0.9127 | 0.0523 | 0.7740 | 0.4016 | 0.8309 | 0.7587 | 0.8599 | 0.9036 |
97
+ | 0.747 | 4.5 | 580 | 0.3340 | 0.6764 | 0.7382 | 0.9130 | 0.9680 | 0.0617 | 0.9125 | 0.5379 | 0.8957 | 0.8362 | 0.9556 | 0.9146 | 0.0614 | 0.7948 | 0.5336 | 0.8279 | 0.7439 | 0.8588 | 0.9061 |
98
+ | 0.343 | 4.65 | 600 | 0.3065 | 0.6853 | 0.7474 | 0.9139 | 0.9647 | 0.0666 | 0.8925 | 0.5978 | 0.9128 | 0.8429 | 0.9542 | 0.9171 | 0.0664 | 0.7909 | 0.5886 | 0.8287 | 0.7436 | 0.8621 | 0.9074 |
99
+ | 0.2358 | 4.81 | 620 | 0.3229 | 0.6916 | 0.7504 | 0.9144 | 0.9719 | 0.0880 | 0.8895 | 0.6099 | 0.8976 | 0.8312 | 0.9651 | 0.9108 | 0.0874 | 0.7855 | 0.6005 | 0.8332 | 0.7563 | 0.8674 | 0.9080 |
100
+ | 0.3649 | 4.96 | 640 | 0.3026 | 0.7034 | 0.7644 | 0.9151 | 0.9686 | 0.1640 | 0.8804 | 0.6447 | 0.9148 | 0.8220 | 0.9562 | 0.9129 | 0.1617 | 0.7918 | 0.6134 | 0.8333 | 0.7502 | 0.8606 | 0.9101 |
101
+ | 0.201 | 5.12 | 660 | 0.2903 | 0.7089 | 0.7678 | 0.9194 | 0.9663 | 0.1156 | 0.9208 | 0.6627 | 0.9029 | 0.8379 | 0.9684 | 0.9153 | 0.1148 | 0.8061 | 0.6444 | 0.8451 | 0.7716 | 0.8648 | 0.9138 |
102
+ | 1.1077 | 5.27 | 680 | 0.2596 | 0.7189 | 0.7752 | 0.9221 | 0.9746 | 0.2053 | 0.8895 | 0.6365 | 0.9112 | 0.8378 | 0.9713 | 0.9192 | 0.2016 | 0.8009 | 0.6199 | 0.8479 | 0.7545 | 0.8883 | 0.9176 |
103
+ | 0.2368 | 5.43 | 700 | 0.2479 | 0.7271 | 0.7986 | 0.9213 | 0.9727 | 0.3222 | 0.8877 | 0.7104 | 0.9135 | 0.8259 | 0.9580 | 0.9184 | 0.3114 | 0.8003 | 0.5698 | 0.8370 | 0.7636 | 0.8894 | 0.9184 |
104
+ | 0.2576 | 5.58 | 720 | 0.3153 | 0.7171 | 0.7772 | 0.9173 | 0.9772 | 0.1874 | 0.8721 | 0.7060 | 0.9007 | 0.8399 | 0.9570 | 0.9152 | 0.1839 | 0.7926 | 0.6778 | 0.8408 | 0.7455 | 0.8637 | 0.9127 |
105
+ | 0.3873 | 5.74 | 740 | 0.3024 | 0.7395 | 0.7985 | 0.9212 | 0.9687 | 0.3518 | 0.9369 | 0.6845 | 0.9092 | 0.7793 | 0.9589 | 0.9208 | 0.3370 | 0.8203 | 0.6516 | 0.8367 | 0.7479 | 0.8622 | 0.9184 |
106
+ | 0.2281 | 5.89 | 760 | 0.2583 | 0.7502 | 0.8104 | 0.9227 | 0.9699 | 0.4031 | 0.9094 | 0.7032 | 0.9107 | 0.8210 | 0.9553 | 0.9229 | 0.3810 | 0.8150 | 0.6723 | 0.8431 | 0.7563 | 0.8606 | 0.9205 |
107
+ | 0.2202 | 6.05 | 780 | 0.3227 | 0.7612 | 0.8314 | 0.9205 | 0.9525 | 0.5297 | 0.9437 | 0.7038 | 0.8889 | 0.8332 | 0.9677 | 0.9253 | 0.4917 | 0.7900 | 0.6693 | 0.8338 | 0.7585 | 0.8599 | 0.9197 |
108
+ | 0.292 | 6.2 | 800 | 0.2558 | 0.7614 | 0.8266 | 0.9283 | 0.9710 | 0.4248 | 0.8964 | 0.7571 | 0.9185 | 0.8553 | 0.9629 | 0.9220 | 0.4076 | 0.8202 | 0.6464 | 0.8473 | 0.7915 | 0.8946 | 0.9264 |
109
+ | 0.1304 | 6.36 | 820 | 0.2441 | 0.7386 | 0.8067 | 0.9244 | 0.9764 | 0.3536 | 0.9007 | 0.6908 | 0.9019 | 0.8823 | 0.9412 | 0.9109 | 0.3357 | 0.8088 | 0.5524 | 0.8277 | 0.8106 | 0.9244 | 0.9221 |
110
+ | 0.1664 | 6.51 | 840 | 0.2565 | 0.7685 | 0.8302 | 0.9282 | 0.9728 | 0.4257 | 0.8564 | 0.7880 | 0.9277 | 0.8793 | 0.9614 | 0.9244 | 0.3944 | 0.8006 | 0.7192 | 0.8439 | 0.7941 | 0.9032 | 0.9263 |
111
+ | 0.4424 | 6.67 | 860 | 0.2667 | 0.7808 | 0.8611 | 0.9332 | 0.9680 | 0.5948 | 0.9061 | 0.7883 | 0.9039 | 0.8938 | 0.9727 | 0.9362 | 0.5495 | 0.8165 | 0.6008 | 0.8453 | 0.8086 | 0.9083 | 0.9326 |
112
+ | 0.3753 | 6.82 | 880 | 0.2585 | 0.7353 | 0.8117 | 0.9236 | 0.9765 | 0.4103 | 0.8985 | 0.7286 | 0.9126 | 0.7922 | 0.9633 | 0.9221 | 0.3532 | 0.8025 | 0.5636 | 0.8374 | 0.7631 | 0.9054 | 0.9215 |
113
+ | 0.2642 | 6.98 | 900 | 0.2955 | 0.7734 | 0.8443 | 0.9247 | 0.9586 | 0.5628 | 0.9093 | 0.7641 | 0.9085 | 0.8357 | 0.9708 | 0.9240 | 0.5068 | 0.8133 | 0.6949 | 0.8429 | 0.7634 | 0.8685 | 0.9238 |
114
+ | 0.5008 | 7.13 | 920 | 0.3048 | 0.7703 | 0.8430 | 0.9262 | 0.9712 | 0.5688 | 0.8871 | 0.7660 | 0.9077 | 0.8329 | 0.9676 | 0.9260 | 0.5015 | 0.8170 | 0.6626 | 0.8502 | 0.7697 | 0.8651 | 0.9251 |
115
+ | 0.169 | 7.29 | 940 | 0.2969 | 0.7778 | 0.8528 | 0.9252 | 0.9644 | 0.6690 | 0.9288 | 0.7274 | 0.8966 | 0.8274 | 0.9559 | 0.9263 | 0.5909 | 0.8081 | 0.6410 | 0.8444 | 0.7733 | 0.8608 | 0.9246 |
116
+ | 0.2429 | 7.44 | 960 | 0.3385 | 0.7906 | 0.8551 | 0.9283 | 0.9626 | 0.6420 | 0.9047 | 0.7576 | 0.9131 | 0.8281 | 0.9776 | 0.9322 | 0.5836 | 0.8160 | 0.7156 | 0.8415 | 0.7752 | 0.8701 | 0.9276 |
117
+ | 0.1542 | 7.6 | 980 | 0.3259 | 0.7882 | 0.8574 | 0.9264 | 0.9646 | 0.6734 | 0.9031 | 0.7509 | 0.9007 | 0.8403 | 0.9686 | 0.9298 | 0.5949 | 0.8138 | 0.7056 | 0.8366 | 0.7707 | 0.8663 | 0.9258 |
118
+ | 0.1378 | 7.75 | 1000 | 0.3257 | 0.7815 | 0.8589 | 0.9249 | 0.9675 | 0.6849 | 0.8784 | 0.7864 | 0.9151 | 0.8219 | 0.9580 | 0.9265 | 0.5842 | 0.8076 | 0.6769 | 0.8375 | 0.7767 | 0.8610 | 0.9242 |
119
+ | 0.2144 | 7.91 | 1020 | 0.3347 | 0.7889 | 0.8561 | 0.9276 | 0.9578 | 0.6604 | 0.9128 | 0.7455 | 0.9176 | 0.8261 | 0.9729 | 0.9317 | 0.5932 | 0.8189 | 0.7046 | 0.8416 | 0.7636 | 0.8688 | 0.9270 |
120
+ | 0.1011 | 8.06 | 1040 | 0.3099 | 0.7831 | 0.8546 | 0.9267 | 0.9655 | 0.6394 | 0.8900 | 0.7685 | 0.9091 | 0.8402 | 0.9695 | 0.9289 | 0.5594 | 0.8137 | 0.6999 | 0.8434 | 0.7682 | 0.8685 | 0.9260 |
121
+ | 0.1543 | 8.22 | 1060 | 0.3291 | 0.7921 | 0.8667 | 0.9294 | 0.9667 | 0.7434 | 0.9074 | 0.7434 | 0.9025 | 0.8251 | 0.9781 | 0.9357 | 0.6127 | 0.8145 | 0.6936 | 0.8460 | 0.7703 | 0.8720 | 0.9289 |
122
+ | 0.2624 | 8.37 | 1080 | 0.3284 | 0.7884 | 0.8593 | 0.9247 | 0.9644 | 0.6802 | 0.8663 | 0.7915 | 0.9233 | 0.8317 | 0.9580 | 0.9297 | 0.5924 | 0.8031 | 0.7343 | 0.8332 | 0.7633 | 0.8631 | 0.9241 |
123
+ | 0.1817 | 8.53 | 1100 | 0.3187 | 0.7848 | 0.8557 | 0.9255 | 0.9705 | 0.6361 | 0.9041 | 0.7843 | 0.8918 | 0.8460 | 0.9573 | 0.9265 | 0.5584 | 0.8179 | 0.7210 | 0.8371 | 0.7698 | 0.8626 | 0.9248 |
124
+ | 0.1702 | 8.68 | 1120 | 0.3412 | 0.7737 | 0.8545 | 0.9252 | 0.9680 | 0.6271 | 0.8745 | 0.8030 | 0.9108 | 0.8296 | 0.9682 | 0.9285 | 0.5294 | 0.8047 | 0.6748 | 0.8430 | 0.7686 | 0.8673 | 0.9245 |
125
+
126
+
127
+ ### Framework versions
128
+
129
+ - Transformers 4.37.0
130
+ - Pytorch 2.1.2
131
+ - Datasets 2.18.0
132
+ - Tokenizers 0.15.1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
config.json ADDED
@@ -0,0 +1,88 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "nvidia/segformer-b5-finetuned-ade-640-640",
3
+ "architectures": [
4
+ "SegformerForSemanticSegmentation"
5
+ ],
6
+ "attention_probs_dropout_prob": 0.0,
7
+ "classifier_dropout_prob": 0.1,
8
+ "decoder_hidden_size": 768,
9
+ "depths": [
10
+ 3,
11
+ 6,
12
+ 40,
13
+ 3
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": "water",
32
+ "1": "whitewater",
33
+ "2": "sediment",
34
+ "3": "other_natural_terrain",
35
+ "4": "vegetation",
36
+ "5": "development",
37
+ "6": "unknown"
38
+ },
39
+ "image_size": 224,
40
+ "initializer_range": 0.02,
41
+ "label2id": {
42
+ "development": 5,
43
+ "other_natural_terrain": 3,
44
+ "sediment": 2,
45
+ "unknown": 6,
46
+ "vegetation": 4,
47
+ "water": 0,
48
+ "whitewater": 1
49
+ },
50
+ "layer_norm_eps": 1e-06,
51
+ "mlp_ratios": [
52
+ 4,
53
+ 4,
54
+ 4,
55
+ 4
56
+ ],
57
+ "model_type": "segformer",
58
+ "num_attention_heads": [
59
+ 1,
60
+ 2,
61
+ 5,
62
+ 8
63
+ ],
64
+ "num_channels": 3,
65
+ "num_encoder_blocks": 4,
66
+ "patch_sizes": [
67
+ 7,
68
+ 3,
69
+ 3,
70
+ 3
71
+ ],
72
+ "reshape_last_stage": true,
73
+ "semantic_loss_ignore_index": 255,
74
+ "sr_ratios": [
75
+ 8,
76
+ 4,
77
+ 2,
78
+ 1
79
+ ],
80
+ "strides": [
81
+ 4,
82
+ 2,
83
+ 2,
84
+ 2
85
+ ],
86
+ "torch_dtype": "float32",
87
+ "transformers_version": "4.37.0"
88
+ }
model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:55d8b33ebfa66817e1fdf1a932d894da305e02c81de80250e147e1a3516dee2b
3
+ size 338543820
runs/Mar06_14-50-05_c8ef0f2261eb/events.out.tfevents.1709736608.c8ef0f2261eb.26.0 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:66c73faa7ebad685574e3f07a42126ebaee7f59acb1591b1adb8b2f4b010a261
3
+ size 256056
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ce4b760c648af90fc190b74bb7f52a960f6cf28a2b12c84bc0a27aa786bd43b5
3
+ size 4792