Commit From AutoTrain

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.bin.* filter=lfs diff=lfs merge=lfs -text
+*.tar.gz filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,56 @@
+---
+tags:
+- autotrain
+- text-classification
+language:
+- unk
+widget:
+- text: "I love AutoTrain 🤗"
+datasets:
+- Sushovan/autotrain-data-test-text-classification
+co2_eq_emissions:
+  emissions: 3.2260052742267447
+---
+
+# Model Trained Using AutoTrain
+
+- Problem type: Multi-class Classification
+- Model ID: 3175589570
+- CO2 Emissions (in grams): 3.2260
+
+## Validation Metrics
+
+- Loss: 1.111
+- Accuracy: 0.665
+- Macro F1: 0.424
+- Micro F1: 0.665
+- Weighted F1: 0.638
+- Macro Precision: 0.427
+- Micro Precision: 0.665
+- Weighted Precision: 0.622
+- Macro Recall: 0.434
+- Micro Recall: 0.665
+- Weighted Recall: 0.665
+
+
+## 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/Sushovan/autotrain-test-text-classification-3175589570
+```
+
+Or Python API:
+
+```
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+
+model = AutoModelForSequenceClassification.from_pretrained("Sushovan/autotrain-test-text-classification-3175589570", use_auth_token=True)
+
+tokenizer = AutoTokenizer.from_pretrained("Sushovan/autotrain-test-text-classification-3175589570", use_auth_token=True)
+
+inputs = tokenizer("I love AutoTrain", return_tensors="pt")
+
+outputs = model(**inputs)
+```

config.json

@@ -0,0 +1,70 @@
+{
+  "_name_or_path": "AutoTrain",
+  "_num_labels": 18,
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "Blouses",
+    "1": "Dresses",
+    "2": "Fine gauge",
+    "3": "Intimates",
+    "4": "Jackets",
+    "5": "Jeans",
+    "6": "Knits",
+    "7": "Layering",
+    "8": "Legwear",
+    "9": "Lounge",
+    "10": "Outerwear",
+    "11": "Pants",
+    "12": "Shorts",
+    "13": "Skirts",
+    "14": "Sleep",
+    "15": "Sweaters",
+    "16": "Swim",
+    "17": "Trend"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "Blouses": 0,
+    "Dresses": 1,
+    "Fine gauge": 2,
+    "Intimates": 3,
+    "Jackets": 4,
+    "Jeans": 5,
+    "Knits": 6,
+    "Layering": 7,
+    "Legwear": 8,
+    "Lounge": 9,
+    "Outerwear": 10,
+    "Pants": 11,
+    "Shorts": 12,
+    "Skirts": 13,
+    "Sleep": 14,
+    "Sweaters": 15,
+    "Swim": 16,
+    "Trend": 17
+  },
+  "layer_norm_eps": 1e-12,
+  "max_length": 192,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "padding": "max_length",
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.25.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 28996
+}

pytorch_model.bin

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special_tokens_map.json

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+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer.json

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tokenizer_config.json

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+{
+  "cls_token": "[CLS]",
+  "do_lower_case": false,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "name_or_path": "AutoTrain",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "special_tokens_map_file": null,
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}