Hugging Face's logo

Genereux-akotenou
/
genomics-tf-prediction

Tabular Classification
Keras
biology
Model card Files Community
genomics-tf-prediction / Train-Reports /CAMTA /report_7C1YZ8T2.html
Genereux-akotenou's picture
Genereux-akotenou
add train reports
0318fb1 verified
raw
history blame contribute delete
171 kB
<html>
<head>
<title>GENE_FAMILY: CAMTA</title>
<style>
body { font-family: Arial, sans-serif; }
.container { border: 2px solid #ddd; margin: 20px; padding: 20px; }
.header { padding: 0.6em; background-color: #ffdddd; font-weight: bold; }
.title { padding: 0.6em; background-color: #80c4e6bd; font-weight: bold; }
.section { padding: 10px; }
.metrics { display: flex; }
.metrics ul { list-style: none; padding: 0; }
.metrics ul + ul { margin-left: 2em; }
.confusion-matrix img, .learning-curve img { width: 100%; max-width: 565px; }
.class_dist { width: 20em; }
.mod_sum { margin-bottom: 2em; }
</style>
</head>
<body>
<div class="container title">
<h3>GENE_FAMILY: <a href='https://planttfdb.gao-lab.org/family.php?fam=CAMTA' target='_blank'>CAMTA</a></h3>
</div>
<div class="container">
<div class="header">MODEL: FEEDFORWARD_k2</div>
<div style="display: flex;">
<div class="section">
<h2 class='mod_sum'>Model Architecture</h2>
<pre>Model: "FEEDFORWARD_k2"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓
┃ Layer (type) ┃ Output Shape ┃ Param # ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩
│ dense (Dense) │ (None, 256) │ 113,152 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dropout (Dropout) │ (None, 256) │ 0 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dense_1 (Dense) │ (None, 128) │ 32,896 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dropout_1 (Dropout) │ (None, 128) │ 0 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dense_2 (Dense) │ (None, 64) │ 8,256 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dropout_2 (Dropout) │ (None, 64) │ 0 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dense_3 (Dense) │ (None, 32) │ 2,080 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dropout_3 (Dropout) │ (None, 32) │ 0 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dense_4 (Dense) │ (None, 1) │ 33 │
└──────────────────────────────────────┴─────────────────────────────┴─────────────────┘
Total params: 469,253 (1.79 MB)
Trainable params: 156,417 (611.00 KB)
Non-trainable params: 0 (0.00 B)
Optimizer params: 312,836 (1.19 MB)
</pre>
</div>
<div class="section learning-curve">
<h2>Learning Curve</h2>
<img src="data:image/png;base64,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" alt="Learning Curve">
</div>
</div>
<div style="display: flex;">
<div class="section class_dist">
<h2>Class Distribution</h2>
<pre> Count Percentage
class
1 1343 50.51
0 1316 49.49</pre>
<h3>Additional Metrics</h3>
<ul>
<li>Total Samples: 2659</li>
<li>Imbalance Ratio: 1.02</li>
</ul>
</div>
<div class="section">
<h2>Classification Report</h2>
<pre> precision recall f1-score support
Class 0 0.9962 0.9848 0.9904 263
Class 1 0.9853 0.9963 0.9908 269
accuracy 0.9906 532
macro avg 0.9907 0.9905 0.9906 532
weighted avg 0.9907 0.9906 0.9906 532
</pre>
<h3>Metrics</h3>
<div class="metrics">
<ul>
<li>True Positives (TP): 268</li>
<li>True Negatives (TN): 259</li>
</ul>
<ul>
<li>False Positives (FP): 4</li>
<li>False Negatives (FN): 1</li>
</ul>
</div>
</div>
<div class="section confusion-matrix">
<h2>Confusion Matrix</h2>
<img src="data:image/png;base64,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" alt="Confusion Matrix">
</div>
</div>
</div>
<div class="container">
<div class="header">MODEL: FEEDFORWARD_k3</div>
<div style="display: flex;">
<div class="section">
<h2 class='mod_sum'>Model Architecture</h2>
<pre>Model: "FEEDFORWARD_k3"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓
┃ Layer (type) ┃ Output Shape ┃ Param # ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩
│ dense_5 (Dense) │ (None, 256) │ 2,199,040 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dropout_4 (Dropout) │ (None, 256) │ 0 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dense_6 (Dense) │ (None, 128) │ 32,896 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dropout_5 (Dropout) │ (None, 128) │ 0 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dense_7 (Dense) │ (None, 64) │ 8,256 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dropout_6 (Dropout) │ (None, 64) │ 0 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dense_8 (Dense) │ (None, 32) │ 2,080 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dropout_7 (Dropout) │ (None, 32) │ 0 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dense_9 (Dense) │ (None, 1) │ 33 │
└──────────────────────────────────────┴─────────────────────────────┴─────────────────┘
Total params: 6,726,917 (25.66 MB)
Trainable params: 2,242,305 (8.55 MB)
Non-trainable params: 0 (0.00 B)
Optimizer params: 4,484,612 (17.11 MB)
</pre>
</div>
<div class="section learning-curve">
<h2>Learning Curve</h2>
<img src="data:image/png;base64,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" alt="Learning Curve">
</div>
</div>
<div style="display: flex;">
<div class="section class_dist">
<h2>Class Distribution</h2>
<pre> Count Percentage
class
1 1343 50.51
0 1316 49.49</pre>
<h3>Additional Metrics</h3>
<ul>
<li>Total Samples: 2659</li>
<li>Imbalance Ratio: 1.02</li>
</ul>
</div>
<div class="section">
<h2>Classification Report</h2>
<pre> precision recall f1-score support
Class 0 0.9813 1.0000 0.9906 263
Class 1 1.0000 0.9814 0.9906 269
accuracy 0.9906 532
macro avg 0.9907 0.9907 0.9906 532
weighted avg 0.9908 0.9906 0.9906 532
</pre>
<h3>Metrics</h3>
<div class="metrics">
<ul>
<li>True Positives (TP): 264</li>
<li>True Negatives (TN): 263</li>
</ul>
<ul>
<li>False Positives (FP): 0</li>
<li>False Negatives (FN): 5</li>
</ul>
</div>
</div>
<div class="section confusion-matrix">
<h2>Confusion Matrix</h2>
<img src="data:image/png;base64,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" alt="Confusion Matrix">
</div>
</div>
</div>
<div class="container">
<div class="header">MODEL: FEEDFORWARD_k4</div>
<div style="display: flex;">
<div class="section">
<h2 class='mod_sum'>Model Architecture</h2>
<pre>Model: "FEEDFORWARD_k4"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓
┃ Layer (type) ┃ Output Shape ┃ Param # ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩
│ dense_10 (Dense) │ (None, 256) │ 33,357,056 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dropout_8 (Dropout) │ (None, 256) │ 0 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dense_11 (Dense) │ (None, 128) │ 32,896 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dropout_9 (Dropout) │ (None, 128) │ 0 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dense_12 (Dense) │ (None, 64) │ 8,256 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dropout_10 (Dropout) │ (None, 64) │ 0 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dense_13 (Dense) │ (None, 1) │ 65 │
└──────────────────────────────────────┴─────────────────────────────┴─────────────────┘
Total params: 100,194,821 (382.21 MB)
Trainable params: 33,398,273 (127.40 MB)
Non-trainable params: 0 (0.00 B)
Optimizer params: 66,796,548 (254.81 MB)
</pre>
</div>
<div class="section learning-curve">
<h2>Learning Curve</h2>
<img src="data:image/png;base64,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" alt="Learning Curve">
</div>
</div>
<div style="display: flex;">
<div class="section class_dist">
<h2>Class Distribution</h2>
<pre> Count Percentage
class
1 1343 50.51
0 1316 49.49</pre>
<h3>Additional Metrics</h3>
<ul>
<li>Total Samples: 2659</li>
<li>Imbalance Ratio: 1.02</li>
</ul>
</div>
<div class="section">
<h2>Classification Report</h2>
<pre> precision recall f1-score support
Class 0 0.9850 1.0000 0.9925 263
Class 1 1.0000 0.9851 0.9925 269
accuracy 0.9925 532
macro avg 0.9925 0.9926 0.9925 532
weighted avg 0.9926 0.9925 0.9925 532
</pre>
<h3>Metrics</h3>
<div class="metrics">
<ul>
<li>True Positives (TP): 265</li>
<li>True Negatives (TN): 263</li>
</ul>
<ul>
<li>False Positives (FP): 0</li>
<li>False Negatives (FN): 4</li>
</ul>
</div>
</div>
<div class="section confusion-matrix">
<h2>Confusion Matrix</h2>
<img src="data:image/png;base64,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" alt="Confusion Matrix">
</div>
</div>
</div>
</body>
</html>