Update README.md
Browse files
README.md
CHANGED
@@ -1,199 +1,94 @@
|
|
1 |
---
|
2 |
-
|
3 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
4 |
---
|
5 |
|
6 |
-
#
|
7 |
|
8 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
9 |
|
|
|
10 |
|
|
|
11 |
|
12 |
-
|
13 |
|
14 |
-
|
15 |
|
16 |
-
|
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 |
-
|
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 |
-
|
29 |
|
30 |
-
|
31 |
|
32 |
-
|
33 |
-
- **Paper [optional]:** [More Information Needed]
|
34 |
-
- **Demo [optional]:** [More Information Needed]
|
35 |
|
36 |
-
##
|
37 |
|
38 |
-
|
39 |
|
40 |
-
|
41 |
|
42 |
-
|
43 |
|
44 |
-
|
45 |
|
46 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
47 |
|
48 |
-
|
49 |
|
50 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
51 |
|
52 |
-
### Out-of-Scope Use
|
53 |
|
54 |
-
|
55 |
|
56 |
-
|
57 |
-
|
58 |
-
|
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: apache-2.0
|
3 |
+
base_model: microsoft/beit-large-patch16-224-pt22k-ft22k
|
4 |
+
tags:
|
5 |
+
- generated_from_trainer
|
6 |
+
metrics:
|
7 |
+
- pearsonr
|
8 |
+
- r_squared
|
9 |
+
model-index:
|
10 |
+
- name: motes_mtci_microsoft-beit-large-patch16-224-pt22k-ft22k
|
11 |
+
results: []
|
12 |
---
|
13 |
|
14 |
+
# Ocsai-D Web
|
15 |
|
16 |
+
This model is a trained model for scoring creativity - specifically figural (drawing-based) originality scoring. It is a fine-tuned version of [beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224-pt22k-ft22k).
|
17 |
+
It achieves the following results on the evaluation set:
|
18 |
+
- Loss: 0.0055
|
19 |
+
- Mse: 0.0055
|
20 |
+
- Pearsonr: 0.8745
|
21 |
+
- R2: 0.7224
|
22 |
+
- Rmse: 0.0745
|
23 |
|
24 |
+
It can be tried at <https://openscoring.du.edu/draw>.
|
25 |
|
26 |
+
## Model description
|
27 |
|
28 |
+
See the pre-print:
|
29 |
|
30 |
+
Acar, S.^, Organisciak, P.^, & Dumas, D. (2023). Automated Scoring of Figural Tests of Creativity with Computer Vision. http://dx.doi.org/10.13140/RG.2.2.26865.25444
|
31 |
|
32 |
+
*^Authors contributed equally.*
|
33 |
|
|
|
34 |
|
35 |
+
## Intended uses & limitations
|
|
|
|
|
|
|
|
|
|
|
|
|
36 |
|
37 |
+
This model judges the originality of figural drawings. There are some limitations.
|
38 |
|
39 |
+
First, there is a confound with elaboration - drawing more leads - partially - to higher originality.
|
40 |
|
41 |
+
Secondly, the training is specific to one test, and mileage may vary on other images.
|
|
|
|
|
42 |
|
43 |
+
## Training and evaluation data
|
44 |
|
45 |
+
This is trained on the Multi-Trial Creative Ideation task (MTCI; [Barbot 2018](https://pubmed.ncbi.nlm.nih.gov/30618952/)), with the [data](https://osf.io/kqn9v/) from Patterson et al. ([2023](https://doi.org/10.31234/osf.io/t63dm)).
|
46 |
|
47 |
+
For Ocsai-Web, we used a larger training split, 95%, and bound zero-originality images to zero.
|
48 |
|
49 |
+
## Training procedure
|
50 |
|
51 |
+
### Training hyperparameters
|
52 |
|
53 |
+
The following hyperparameters were used during training:
|
54 |
+
- learning_rate: 5e-05
|
55 |
+
- train_batch_size: 20
|
56 |
+
- eval_batch_size: 20
|
57 |
+
- seed: 42
|
58 |
+
- gradient_accumulation_steps: 8
|
59 |
+
- total_train_batch_size: 160
|
60 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
61 |
+
- lr_scheduler_type: linear
|
62 |
+
- lr_scheduler_warmup_ratio: 0.2
|
63 |
+
- num_epochs: 12
|
64 |
|
65 |
+
### Training results
|
66 |
|
67 |
+
| Training Loss | Epoch | Step | Validation Loss | Mse | Pearsonr | R2 | Rmse |
|
68 |
+
|:-------------:|:------:|:----:|:---------------:|:------:|:--------:|:-------:|:------:|
|
69 |
+
| 0.0728 | 0.3992 | 25 | 0.0141 | 0.0141 | 0.6466 | -0.0091 | 0.1189 |
|
70 |
+
| 0.0137 | 0.7984 | 50 | 0.0094 | 0.0094 | 0.7812 | 0.0650 | 0.0968 |
|
71 |
+
| 0.0153 | 1.1976 | 75 | 0.0118 | 0.0118 | 0.8137 | 0.1092 | 0.1087 |
|
72 |
+
| 0.0155 | 1.5968 | 100 | 0.0168 | 0.0168 | 0.8303 | -0.3131 | 0.1295 |
|
73 |
+
| 0.0157 | 1.9960 | 125 | 0.0080 | 0.0080 | 0.8347 | 0.2944 | 0.0893 |
|
74 |
+
| 0.0087 | 2.3952 | 150 | 0.0068 | 0.0068 | 0.8488 | 0.5258 | 0.0827 |
|
75 |
+
| 0.0078 | 2.7944 | 175 | 0.0093 | 0.0093 | 0.8541 | 0.3130 | 0.0963 |
|
76 |
+
| 0.0079 | 3.1936 | 200 | 0.0092 | 0.0092 | 0.8604 | 0.3562 | 0.0960 |
|
77 |
+
| 0.0073 | 3.5928 | 225 | 0.0076 | 0.0076 | 0.8684 | 0.5507 | 0.0871 |
|
78 |
+
| 0.007 | 3.9920 | 250 | 0.0082 | 0.0082 | 0.8662 | 0.5539 | 0.0904 |
|
79 |
+
| 0.0055 | 4.3912 | 275 | 0.0055 | 0.0055 | 0.8727 | 0.6912 | 0.0744 |
|
80 |
+
| 0.0042 | 4.7904 | 300 | 0.0060 | 0.0060 | 0.8737 | 0.6844 | 0.0773 |
|
81 |
+
| 0.0037 | 5.1896 | 325 | 0.0061 | 0.0061 | 0.8702 | 0.6496 | 0.0781 |
|
82 |
+
| 0.0034 | 5.5888 | 350 | 0.0061 | 0.0061 | 0.8707 | 0.6426 | 0.0781 |
|
83 |
+
| 0.0031 | 5.9880 | 375 | 0.0057 | 0.0057 | 0.8717 | 0.7266 | 0.0757 |
|
84 |
+
| 0.0023 | 6.3872 | 400 | 0.0056 | 0.0056 | 0.8716 | 0.7084 | 0.0749 |
|
85 |
+
| 0.002 | 6.7864 | 425 | 0.0056 | 0.0056 | 0.8708 | 0.6710 | 0.0745 |
|
86 |
+
| 0.0018 | 7.1856 | 450 | 0.0055 | 0.0055 | 0.8745 | 0.7224 | 0.0745 |
|
87 |
|
|
|
88 |
|
89 |
+
### Framework versions
|
90 |
|
91 |
+
- Transformers 4.40.0
|
92 |
+
- Pytorch 2.2.1+cu121
|
93 |
+
- Datasets 2.19.0
|
94 |
+
- Tokenizers 0.19.1
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|