Hasano20 commited on
Commit
2c5d569
1 Parent(s): 07c9321

End of training

Browse files
Files changed (4) hide show
  1. README.md +84 -196
  2. config.json +80 -0
  3. model.safetensors +3 -0
  4. training_args.bin +3 -0
README.md CHANGED
@@ -1,199 +1,87 @@
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]
 
1
  ---
2
+ license: other
3
+ base_model: nvidia/mit-b5
4
+ tags:
5
+ - vision
6
+ - image-segmentation
7
+ - generated_from_trainer
8
+ model-index:
9
+ - name: SegFormer_mit-b5_Clean-Set3_Augmented_Medium
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_mit-b5_Clean-Set3_Augmented_Medium
17
+
18
+ This model is a fine-tuned version of [nvidia/mit-b5](https://huggingface.co/nvidia/mit-b5) on the Hasano20/Clean-Set3 dataset.
19
+ It achieves the following results on the evaluation set:
20
+ - Loss: 0.0205
21
+ - Mean Iou: 0.9709
22
+ - Mean Accuracy: 0.9837
23
+ - Overall Accuracy: 0.9928
24
+ - Accuracy Background: 0.9979
25
+ - Accuracy Melt: 0.9593
26
+ - Accuracy Substrate: 0.9938
27
+ - Iou Background: 0.9927
28
+ - Iou Melt: 0.9315
29
+ - Iou Substrate: 0.9885
30
+
31
+ ## Model description
32
+
33
+ More information needed
34
+
35
+ ## Intended uses & limitations
36
+
37
+ More information needed
38
+
39
+ ## Training and evaluation data
40
+
41
+ More information needed
42
+
43
+ ## Training procedure
44
+
45
+ ### Training hyperparameters
46
+
47
+ The following hyperparameters were used during training:
48
+ - learning_rate: 0.0002
49
+ - train_batch_size: 8
50
+ - eval_batch_size: 8
51
+ - seed: 42
52
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
53
+ - lr_scheduler_type: cosine
54
+ - lr_scheduler_warmup_steps: 100
55
+ - num_epochs: 20
56
+
57
+ ### Training results
58
+
59
+ | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Background | Accuracy Melt | Accuracy Substrate | Iou Background | Iou Melt | Iou Substrate |
60
+ |:-------------:|:------:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:-------------:|:------------------:|:--------------:|:--------:|:-------------:|
61
+ | 0.1481 | 0.3968 | 50 | 0.1951 | 0.7748 | 0.8972 | 0.9261 | 0.9808 | 0.8114 | 0.8996 | 0.9583 | 0.4859 | 0.8802 |
62
+ | 0.1364 | 0.7937 | 100 | 0.0745 | 0.8855 | 0.9155 | 0.9727 | 0.9933 | 0.7647 | 0.9884 | 0.9753 | 0.7206 | 0.9604 |
63
+ | 0.0776 | 1.1905 | 150 | 0.1238 | 0.8046 | 0.8351 | 0.9565 | 0.9922 | 0.5172 | 0.9960 | 0.9754 | 0.5059 | 0.9325 |
64
+ | 0.0851 | 1.5873 | 200 | 0.0878 | 0.8651 | 0.8901 | 0.9687 | 0.9923 | 0.6841 | 0.9940 | 0.9791 | 0.6665 | 0.9498 |
65
+ | 0.1893 | 1.9841 | 250 | 0.0602 | 0.9077 | 0.9628 | 0.9766 | 0.9958 | 0.9233 | 0.9693 | 0.9872 | 0.7755 | 0.9602 |
66
+ | 0.1236 | 2.3810 | 300 | 0.0643 | 0.9042 | 0.9455 | 0.9768 | 0.9971 | 0.8609 | 0.9783 | 0.9758 | 0.7669 | 0.9699 |
67
+ | 0.0809 | 2.7778 | 350 | 0.0387 | 0.9408 | 0.9699 | 0.9857 | 0.9964 | 0.9271 | 0.9862 | 0.9895 | 0.8562 | 0.9769 |
68
+ | 0.0357 | 3.1746 | 400 | 0.0364 | 0.9431 | 0.9701 | 0.9860 | 0.9948 | 0.9274 | 0.9880 | 0.9897 | 0.8629 | 0.9767 |
69
+ | 0.0408 | 3.5714 | 450 | 0.0424 | 0.9349 | 0.9815 | 0.9834 | 0.9936 | 0.9745 | 0.9765 | 0.9904 | 0.8434 | 0.9708 |
70
+ | 0.0973 | 3.9683 | 500 | 0.0541 | 0.9172 | 0.9798 | 0.9785 | 0.9941 | 0.9796 | 0.9655 | 0.9903 | 0.7997 | 0.9615 |
71
+ | 0.0274 | 4.3651 | 550 | 0.0256 | 0.9636 | 0.9830 | 0.9904 | 0.9967 | 0.9629 | 0.9894 | 0.9893 | 0.9170 | 0.9844 |
72
+ | 0.04 | 4.7619 | 600 | 0.0329 | 0.9482 | 0.9696 | 0.9877 | 0.9977 | 0.9210 | 0.9899 | 0.9888 | 0.8743 | 0.9815 |
73
+ | 0.0301 | 5.1587 | 650 | 0.0247 | 0.9609 | 0.9756 | 0.9905 | 0.9975 | 0.9361 | 0.9933 | 0.9917 | 0.9067 | 0.9844 |
74
+ | 0.0137 | 5.5556 | 700 | 0.0214 | 0.9667 | 0.9779 | 0.9919 | 0.9962 | 0.9414 | 0.9962 | 0.9924 | 0.9206 | 0.9870 |
75
+ | 0.019 | 5.9524 | 750 | 0.0243 | 0.9619 | 0.9817 | 0.9907 | 0.9959 | 0.9577 | 0.9915 | 0.9916 | 0.9090 | 0.9851 |
76
+ | 0.021 | 6.3492 | 800 | 0.0200 | 0.9678 | 0.9853 | 0.9920 | 0.9972 | 0.9668 | 0.9917 | 0.9926 | 0.9237 | 0.9871 |
77
+ | 0.0156 | 6.7460 | 850 | 0.0211 | 0.9689 | 0.9813 | 0.9924 | 0.9965 | 0.9520 | 0.9954 | 0.9926 | 0.9259 | 0.9880 |
78
+ | 0.0153 | 7.1429 | 900 | 0.0205 | 0.9685 | 0.9842 | 0.9923 | 0.9970 | 0.9626 | 0.9930 | 0.9930 | 0.9249 | 0.9876 |
79
+ | 0.0125 | 7.5397 | 950 | 0.0205 | 0.9709 | 0.9837 | 0.9928 | 0.9979 | 0.9593 | 0.9938 | 0.9927 | 0.9315 | 0.9885 |
80
+
81
+
82
+ ### Framework versions
83
+
84
+ - Transformers 4.41.2
85
+ - Pytorch 2.0.1+cu117
86
+ - Datasets 2.19.2
87
+ - Tokenizers 0.19.1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
config.json ADDED
@@ -0,0 +1,80 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "nvidia/mit-b5",
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": "background",
32
+ "1": "melt",
33
+ "2": "substrate"
34
+ },
35
+ "image_size": 224,
36
+ "initializer_range": 0.02,
37
+ "label2id": {
38
+ "background": 0,
39
+ "melt": 1,
40
+ "substrate": 2
41
+ },
42
+ "layer_norm_eps": 1e-06,
43
+ "mlp_ratios": [
44
+ 4,
45
+ 4,
46
+ 4,
47
+ 4
48
+ ],
49
+ "model_type": "segformer",
50
+ "num_attention_heads": [
51
+ 1,
52
+ 2,
53
+ 5,
54
+ 8
55
+ ],
56
+ "num_channels": 3,
57
+ "num_encoder_blocks": 4,
58
+ "patch_sizes": [
59
+ 7,
60
+ 3,
61
+ 3,
62
+ 3
63
+ ],
64
+ "reshape_last_stage": true,
65
+ "semantic_loss_ignore_index": 255,
66
+ "sr_ratios": [
67
+ 8,
68
+ 4,
69
+ 2,
70
+ 1
71
+ ],
72
+ "strides": [
73
+ 4,
74
+ 2,
75
+ 2,
76
+ 2
77
+ ],
78
+ "torch_dtype": "float32",
79
+ "transformers_version": "4.41.2"
80
+ }
model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:92b6054c1d994a5214e720ec83b2b703d5f9028a00f947799d0177188bf2ebe9
3
+ size 338531516
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e5771e89590511fdeb975870212ec9741607bc125cda76d1bd2df0d69803209e
3
+ size 4923