sms-spam-classification

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e-hossam96 commited on May 18

Commit

e17517b

1 Parent(s): c14885b

changed classifier model

Browse files

Files changed (6) hide show

Dockerfile +6 -6
README.md +2 -2
main.py +1 -1
pyproject.toml +2 -2
static/index.html +15 -6
uv.lock +29 -27

Dockerfile CHANGED Viewed

@@ -31,13 +31,13 @@ ENV PATH="/app/.venv/bin:$PATH"
 RUN optimum-cli export onnx \
     --opset 14 --task text-classification \
     --framework pt --dtype fp32 --device cpu \
-    --model climatebert/distilroberta-base-climate-sentiment \
-    distilroberta-base-climate-sentiment-onnx
 # model quantization
 RUN optimum-cli onnxruntime quantize --avx512_vnni --per_channel \
-    --onnx_model distilroberta-base-climate-sentiment-onnx \
-    -o distilroberta-base-climate-sentiment-onnx-quantized
 # ------------------------------------------------------- #
@@ -55,8 +55,8 @@ WORKDIR /app
 # copy env files from base to main image
 COPY --from=base /app/.venv ./.venv
-COPY --from=base /app/distilroberta-base-climate-sentiment-onnx-quantized \
-    ./distilroberta-base-climate-sentiment-onnx-quantized
 # add app env var to path
 ENV PATH="/app/.venv/bin:$PATH"

 RUN optimum-cli export onnx \
     --opset 14 --task text-classification \
     --framework pt --dtype fp32 --device cpu \
+    --model mrm8488/bert-tiny-finetuned-sms-spam-detection \
+    bert-tiny-finetuned-sms-spam-detection-onnx
 # model quantization
 RUN optimum-cli onnxruntime quantize --avx512_vnni --per_channel \
+    --onnx_model bert-tiny-finetuned-sms-spam-detection-onnx \
+    -o bert-tiny-finetuned-sms-spam-detection-onnx-quantized
 # ------------------------------------------------------- #
 # copy env files from base to main image
 COPY --from=base /app/.venv ./.venv
+COPY --from=base /app/bert-tiny-finetuned-sms-spam-detection-onnx-quantized \
+    ./bert-tiny-finetuned-sms-spam-detection-onnx-quantized
 # add app env var to path
 ENV PATH="/app/.venv/bin:$PATH"

README.md CHANGED Viewed

@@ -1,5 +1,5 @@
 ---
-title: Climate Sentiment Classification
 emoji: 📚
 colorFrom: blue
 colorTo: gray
@@ -7,5 +7,5 @@ sdk: docker
 app_port: 7860
 pinned: false
 license: mit
-short_description: Optimized Climate Sentiment Classification Pipeline
 ---

 ---
+title: SMS Spam Classification
 emoji: 📚
 colorFrom: blue
 colorTo: gray
 app_port: 7860
 pinned: false
 license: mit
+short_description: Optimized SMS Spam Classification Pipeline
 ---

main.py CHANGED Viewed

@@ -19,7 +19,7 @@ from optimum.onnxruntime import ORTModelForSequenceClassification
 # ----------------------------- #
 transformers.set_seed(42)
-MODEL_NAME = "distilroberta-base-climate-sentiment-onnx-quantized"
 BATCH_PROCESS_INTERVAL = 0.05
 MAX_BATCH_SIZE = 16

 # ----------------------------- #
 transformers.set_seed(42)
+MODEL_NAME = "bert-tiny-finetuned-sms-spam-detection-onnx-quantized"
 BATCH_PROCESS_INTERVAL = 0.05
 MAX_BATCH_SIZE = 16

pyproject.toml CHANGED Viewed

@@ -1,7 +1,7 @@
 [project]
-name = "climate-sentiment-classification"
 version = "0.1.0"
-description = "Optimized Climate Sentiment Classification Pipeline"
 readme = "README.md"
 authors = [
     { name = "e-hossam96", email = "ehh.hossam@gmail.com" }

 [project]
+name = "sms-spam-classification"
 version = "0.1.0"
+description = "Optimized SMS Spam Classification Pipeline"
 readme = "README.md"
 authors = [
     { name = "e-hossam96", email = "ehh.hossam@gmail.com" }

static/index.html CHANGED Viewed

@@ -37,11 +37,12 @@
 <body>
     <div class="container text-center">
         <div class="card p-4 shadow-lg">
-            <h2 class="mb-3">Climate Sentiment Classifier</h2>
-            <p class="mb-4">An optimized sentiment classifier to classify climate-related sentiment in climate-related
-                paragraphs hosted from <a href="https://huggingface.co/climatebert" target="_blank">ClimateBERT</a></p>
-            <input id="sentenceInput" type="text" class="form-control mb-3" placeholder="Enter your sentence here"
-                value="We emitted 13.4 million tonnes CO2 of Scope 2 (indirect emissions), being emissions arising from our consumption of purchased electricity, steam or heat." />
             <button class="btn btn-primary w-100" onclick="classifySentence()">Classify</button>
             <div class="loader" id="loader" style="display:none;">
                 <div class="spinner-border text-primary" role="status">
@@ -76,9 +77,16 @@
                 const endTime = performance.now();  // End timing
                 const elapsed = (endTime - startTime).toFixed(2);
                 // Display label and score in bold, plus elapsed time
                 resultDiv.innerHTML =
-                    `Label: <b>${data.result.label.toUpperCase()}</b> -- ` +
                     `Score: <b>${data.result.score.toFixed(3)}</b> -- ` +
                     `Response Time: <b>${elapsed} ms</b>`;
             } catch (err) {
@@ -96,6 +104,7 @@
             }
         });
     </script>
 </body>

 <body>
     <div class="container text-center">
         <div class="card p-4 shadow-lg">
+            <h2 class="mb-3">SMS Spam Classifier</h2>
+            <p class="mb-4">An optimized sms spam classifier from <a
+                    href="https://huggingface.co/mrm8488/bert-tiny-finetuned-sms-spam-detection" target="_blank">BERT
+                    Tiny SMS Spam Detector</a></p>
+            <input id="sentenceInput" type="text" class="form-control mb-3" placeholder="Enter your sms text here ..."
+                value="FreeMsg Hey there darling it's been 3 week's now and no word back! I'd like some fun you up for it still? Tb ok! XxX std chgs to send, £1.50 to rcv" />
             <button class="btn btn-primary w-100" onclick="classifySentence()">Classify</button>
             <div class="loader" id="loader" style="display:none;">
                 <div class="spinner-border text-primary" role="status">
                 const endTime = performance.now();  // End timing
                 const elapsed = (endTime - startTime).toFixed(2);
+                // Map model labels to custom labels
+                const labelMap = {
+                    "LABEL_0": "SPAM",
+                    "LABEL_1": "HAM"
+                };
+                const mappedLabel = labelMap[data.result.label] || data.result.label;
                 // Display label and score in bold, plus elapsed time
                 resultDiv.innerHTML =
+                    `Label: <b>${mappedLabel}</b> -- ` +
                     `Score: <b>${data.result.score.toFixed(3)}</b> -- ` +
                     `Response Time: <b>${elapsed} ms</b>`;
             } catch (err) {
             }
         });
     </script>
 </body>

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-    { name = "fastapi" },
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