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Commit From AutoTrain

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.gitattributes CHANGED
@@ -25,3 +25,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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README.md ADDED
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+ ---
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+ tags: autotrain
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+ language: en
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+ widget:
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+ - text: "I love AutoTrain 🤗"
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+ datasets:
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+ - deepesh0x/autotrain-data-finetunedmodelbert
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+ co2_eq_emissions: 7.1805069109958835
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+ ---
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+
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+ # Model Trained Using AutoTrain
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+
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+ - Problem type: Binary Classification
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+ - Model ID: 1034335535
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+ - CO2 Emissions (in grams): 7.1805069109958835
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+
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+ ## Validation Metrics
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+
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+ - Loss: 0.05866553634405136
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+ - Accuracy: 0.9793615441722346
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+ - Precision: 0.9811170212765957
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+ - Recall: 0.9819004524886877
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+ - AUC: 0.9976735725727466
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+ - F1: 0.9815085805507516
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+
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+ ## Usage
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+
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+ You can use cURL to access this model:
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+
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+ ```
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+ $ 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/deepesh0x/autotrain-finetunedmodelbert-1034335535
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+ ```
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+
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+ Or Python API:
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+
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+ ```
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+ from transformers import AutoModelForSequenceClassification, AutoTokenizer
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+
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+ model = AutoModelForSequenceClassification.from_pretrained("deepesh0x/autotrain-finetunedmodelbert-1034335535", use_auth_token=True)
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+
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+ tokenizer = AutoTokenizer.from_pretrained("deepesh0x/autotrain-finetunedmodelbert-1034335535", use_auth_token=True)
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+
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+ inputs = tokenizer("I love AutoTrain", return_tensors="pt")
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+
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+ outputs = model(**inputs)
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+ ```
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+ "_name_or_path": "AutoTrain",
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+ "_num_labels": 2,
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+ "activation": "gelu",
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+ "architectures": [
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+ "DistilBertForSequenceClassification"
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+ ],
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+ "attention_dropout": 0.1,
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+ "dim": 768,
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+ "dropout": 0.1,
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+ "finetuning_task": "sst-2",
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+ "hidden_dim": 3072,
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+ "id2label": {
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+ "1": "positive"
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+ },
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+ },
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+ "max_length": 96,
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+ "max_position_embeddings": 512,
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+ "model_type": "distilbert",
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+ "n_heads": 12,
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+ "n_layers": 6,
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+ "output_past": true,
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+ "pad_token_id": 0,
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+ "padding": "max_length",
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+ "problem_type": "single_label_classification",
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+ "qa_dropout": 0.1,
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+ "seq_classif_dropout": 0.2,
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+ "sinusoidal_pos_embds": false,
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+ "tie_weights_": true,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.15.0",
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+ "vocab_size": 30522
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+ }
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tokenizer.json ADDED
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vocab.txt ADDED
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