Commit From AutoTrain

.gitattributes

@@ -25,3 +25,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zstandard filter=lfs diff=lfs merge=lfs -text
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+*.bin.* filter=lfs diff=lfs merge=lfs -text
+*.tar.gz filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,52 @@
+---
+tags: autotrain
+language: ar
+widget:
+- text: "I love AutoTrain 🤗"
+datasets:
+- Yah216/autotrain-data-Poem_Rawiy_detection
+co2_eq_emissions: 1.8046766441629636
+---
+
+# Model Trained Using AutoTrain
+
+- Problem type: Multi-class Classification
+- Model ID: 918730150
+- CO2 Emissions (in grams): 1.8046766441629636
+
+## Validation Metrics
+
+- Loss: 0.398613303899765
+- Accuracy: 0.912351981006084
+- Macro F1: 0.717311758991278
+- Micro F1: 0.912351981006084
+- Weighted F1: 0.9110094798809955
+- Macro Precision: 0.7211917136609866
+- Micro Precision: 0.912351981006084
+- Weighted Precision: 0.9102294701380585
+- Macro Recall: 0.714852045042265
+- Micro Recall: 0.912351981006084
+- Weighted Recall: 0.912351981006084
+
+
+## Usage
+
+You can use cURL to access this model:
+
+```
+$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoTrain"}' https://api-inference.huggingface.co/models/Yah216/autotrain-Poem_Rawiy_detection-918730150
+```
+
+Or Python API:
+
+```
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+
+model = AutoModelForSequenceClassification.from_pretrained("Yah216/autotrain-Poem_Rawiy_detection-918730150", use_auth_token=True)
+
+tokenizer = AutoTokenizer.from_pretrained("Yah216/autotrain-Poem_Rawiy_detection-918730150", use_auth_token=True)
+
+inputs = tokenizer("I love AutoTrain", return_tensors="pt")
+
+outputs = model(**inputs)
+```

config.json

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+{
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+  "architectures": [
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+  "padding": "max_length",
+  "pooler_fc_size": 768,
+  "pooler_num_attention_heads": 12,
+  "pooler_num_fc_layers": 3,
+  "pooler_size_per_head": 128,
+  "pooler_type": "first_token_transform",
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.15.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 50000
+}

pytorch_model.bin

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sample_input.pkl

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special_tokens_map.json

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tokenizer_config.json

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