Commit From AutoTrain

.gitattributes

@@ -32,3 +32,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.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 +1,49 @@
+---
+tags:
+- autotrain
+- token-classification
+language:
+- unk
+widget:
+- text: "I love AutoTrain 🤗"
+datasets:
+- tinyYhorm/autotrain-data-2-xlmr-r
+co2_eq_emissions:
+  emissions: 1.191588461069133
+---
+
+# Model Trained Using AutoTrain
+
+- Problem type: Entity Extraction
+- Model ID: 53880126783
+- CO2 Emissions (in grams): 1.1916
+
+## Validation Metrics
+
+- Loss: 0.186
+- Accuracy: 0.957
+- Precision: 0.872
+- Recall: 0.877
+- F1: 0.875
+
+## 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/tinyYhorm/autotrain-2-xlmr-r-53880126783
+```
+
+Or Python API:
+
+```
+from transformers import AutoModelForTokenClassification, AutoTokenizer
+
+model = AutoModelForTokenClassification.from_pretrained("tinyYhorm/autotrain-2-xlmr-r-53880126783", use_auth_token=True)
+
+tokenizer = AutoTokenizer.from_pretrained("tinyYhorm/autotrain-2-xlmr-r-53880126783", use_auth_token=True)
+
+inputs = tokenizer("I love AutoTrain", return_tensors="pt")
+
+outputs = model(**inputs)
+```

config.json

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+{
+  "_name_or_path": "AutoTrain",
+  "_num_labels": 21,
+  "architectures": [
+    "XLMRobertaForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "B-Case",
+    "1": "B-Commute",
+    "2": "B-Date",
+    "3": "B-H_Address",
+    "4": "B-L_Address",
+    "5": "B-Quarantine",
+    "6": "B-Relationship",
+    "7": "B-Time",
+    "8": "B-Transportation",
+    "9": "B-W_Address",
+    "10": "I-Case",
+    "11": "I-Commute",
+    "12": "I-Date",
+    "13": "I-H_Address",
+    "14": "I-L_Address",
+    "15": "I-Quarantine",
+    "16": "I-Relationship",
+    "17": "I-Time",
+    "18": "I-Transportation",
+    "19": "I-W_Address",
+    "20": "O"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "B-Case": 0,
+    "B-Commute": 1,
+    "B-Date": 2,
+    "B-H_Address": 3,
+    "B-L_Address": 4,
+    "B-Quarantine": 5,
+    "B-Relationship": 6,
+    "B-Time": 7,
+    "B-Transportation": 8,
+    "B-W_Address": 9,
+    "I-Case": 10,
+    "I-Commute": 11,
+    "I-Date": 12,
+    "I-H_Address": 13,
+    "I-L_Address": 14,
+    "I-Quarantine": 15,
+    "I-Relationship": 16,
+    "I-Time": 17,
+    "I-Transportation": 18,
+    "I-W_Address": 19,
+    "O": 20
+  },
+  "layer_norm_eps": 1e-05,
+  "max_length": 192,
+  "max_position_embeddings": 514,
+  "model_type": "xlm-roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "pad_token_id": 1,
+  "padding": "max_length",
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.28.1",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 250002
+}

pytorch_model.bin

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special_tokens_map.json

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+{
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+  "cls_token": "<s>",
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+  "mask_token": {
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tokenizer.json

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tokenizer_config.json

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+{
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "mask_token": {
+    "__type": "AddedToken",
+    "content": "<mask>",
+    "lstrip": true,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "model_max_length": 512,
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "tokenizer_class": "XLMRobertaTokenizer",
+  "unk_token": "<unk>"
+}