BehradG commited on
Commit
379d30f
1 Parent(s): fa38903

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +0 -181
README.md CHANGED
@@ -5,74 +5,6 @@ tags: [Image Classification, MRI, Cancer]
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
@@ -85,116 +17,3 @@ https://huggingface.co/datasets/tanzuhuggingface/brainmri
85
 
86
  The restnet18 model was fin-tuned with P100 GPU for 200 epochs. Both calibration and validation losses decined constantly during the fine-tuning showing no sign of overfitting.
87
  The final accuracy was 97.9%.
88
-
89
- #### Preprocessing [optional]
90
-
91
- [More Information Needed]
92
-
93
-
94
- #### Training Hyperparameters
95
-
96
- - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
97
-
98
- #### Speeds, Sizes, Times [optional]
99
-
100
- <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
101
-
102
- [More Information Needed]
103
-
104
- ## Evaluation
105
-
106
- <!-- This section describes the evaluation protocols and provides the results. -->
107
-
108
- ### Testing Data, Factors & Metrics
109
-
110
- #### Testing Data
111
-
112
- <!-- This should link to a Dataset Card if possible. -->
113
-
114
- [More Information Needed]
115
-
116
- #### Factors
117
-
118
- <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
119
-
120
- [More Information Needed]
121
-
122
- #### Metrics
123
-
124
- <!-- These are the evaluation metrics being used, ideally with a description of why. -->
125
-
126
- [More Information Needed]
127
-
128
- ### Results
129
-
130
- [More Information Needed]
131
-
132
- #### Summary
133
-
134
-
135
-
136
- ## Model Examination [optional]
137
-
138
- <!-- Relevant interpretability work for the model goes here -->
139
-
140
- [More Information Needed]
141
-
142
- ## Environmental Impact
143
-
144
- <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
145
-
146
- 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).
147
-
148
- - **Hardware Type:** [More Information Needed]
149
- - **Hours used:** [More Information Needed]
150
- - **Cloud Provider:** [More Information Needed]
151
- - **Compute Region:** [More Information Needed]
152
- - **Carbon Emitted:** [More Information Needed]
153
-
154
- ## Technical Specifications [optional]
155
-
156
- ### Model Architecture and Objective
157
-
158
- [More Information Needed]
159
-
160
- ### Compute Infrastructure
161
-
162
- [More Information Needed]
163
-
164
- #### Hardware
165
-
166
- [More Information Needed]
167
-
168
- #### Software
169
-
170
- [More Information Needed]
171
-
172
- ## Citation [optional]
173
-
174
- <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
175
-
176
- **BibTeX:**
177
-
178
- [More Information Needed]
179
-
180
- **APA:**
181
-
182
- [More Information Needed]
183
-
184
- ## Glossary [optional]
185
-
186
- <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
187
-
188
- [More Information Needed]
189
-
190
- ## More Information [optional]
191
-
192
- [More Information Needed]
193
-
194
- ## Model Card Authors [optional]
195
-
196
- [More Information Needed]
197
-
198
- ## Model Card Contact
199
-
200
- [More Information Needed]
 
5
 
6
  # Model Card for Model ID
7
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
8
  ## Training Details
9
 
10
  ### Training Data
 
17
 
18
  The restnet18 model was fin-tuned with P100 GPU for 200 epochs. Both calibration and validation losses decined constantly during the fine-tuning showing no sign of overfitting.
19
  The final accuracy was 97.9%.