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Commit From AutoTrain

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README.md ADDED
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+ ---
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+ tags:
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+ - autotrain
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+ - text-classification
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+ language:
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+ - en
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+ widget:
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+ - text: "I love AutoTrain"
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+ datasets:
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+ - Wartb/autotrain-data-component-docs
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+ co2_eq_emissions:
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+ emissions: 0.9488699396895709
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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: Multi-class Classification
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+ - Model ID: 93256145806
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+ - CO2 Emissions (in grams): 0.9489
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+
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+ ## Validation Metrics
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+
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+ - Loss: 0.701
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+ - Accuracy: 0.781
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+ - Macro F1: 0.515
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+ - Micro F1: 0.781
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+ - Weighted F1: 0.723
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+ - Macro Precision: 0.525
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+ - Micro Precision: 0.781
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+ - Weighted Precision: 0.702
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+ - Macro Recall: 0.545
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+ - Micro Recall: 0.781
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+ - Weighted Recall: 0.781
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+
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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/Wartb/autotrain-component-docs-93256145806
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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("Wartb/autotrain-component-docs-93256145806", use_auth_token=True)
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+
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+ tokenizer = AutoTokenizer.from_pretrained("Wartb/autotrain-component-docs-93256145806", 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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+ "_num_labels": 8,
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+ "BertForSequenceClassification"
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+ ],
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+ "gradient_checkpointing": false,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 1024,
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+ "id2label": {
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+ "0": "Component",
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+ "1": "Do example",
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+ "2": "Don't example",
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+ "3": "Educative",
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+ "4": "Rationale",
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+ "5": "States",
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+ "6": "Variant rationale",
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+ "7": "Variants"
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+ "layer_norm_eps": 1e-12,
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+ "max_length": 96,
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+ "max_position_embeddings": 512,
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+ "model_type": "bert",
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+ "num_attention_heads": 16,
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+ "num_hidden_layers": 24,
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+ "pooler_fc_size": 768,
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+ "pooler_num_attention_heads": 12,
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+ "pooler_num_fc_layers": 3,
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+ "pooler_size_per_head": 128,
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+ "pooler_type": "first_token_transform",
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+ "position_embedding_type": "absolute",
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+ "problem_type": "single_label_classification",
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+ "torch_dtype": "float32",
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+ "use_cache": true,
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+ }
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