Commit From AutoNLP

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zstandard filter=lfs diff=lfs merge=lfs -text
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+*.tar.gz filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+tags: autonlp
+language: unk
+widget:
+- text: "I love AutoNLP 🤗"
+datasets:
+- Anamika/autonlp-data-Feedback1
+co2_eq_emissions: 123.88023112815048
+---
+
+# Model Trained Using AutoNLP
+
+- Problem type: Multi-class Classification
+- Model ID: 479512837
+- CO2 Emissions (in grams): 123.88023112815048
+
+## Validation Metrics
+
+- Loss: 0.6220805048942566
+- Accuracy: 0.7961119332705503
+- Macro F1: 0.7616345204219084
+- Micro F1: 0.7961119332705503
+- Weighted F1: 0.795387503907883
+- Macro Precision: 0.782839455262034
+- Micro Precision: 0.7961119332705503
+- Weighted Precision: 0.7992606754484262
+- Macro Recall: 0.7451485972167191
+- Micro Recall: 0.7961119332705503
+- Weighted Recall: 0.7961119332705503
+
+
+## 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 AutoNLP"}' https://api-inference.huggingface.co/models/Anamika/autonlp-Feedback1-479512837
+```
+
+Or Python API:
+
+```
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+
+model = AutoModelForSequenceClassification.from_pretrained("Anamika/autonlp-Feedback1-479512837", use_auth_token=True)
+
+tokenizer = AutoTokenizer.from_pretrained("Anamika/autonlp-Feedback1-479512837", use_auth_token=True)
+
+inputs = tokenizer("I love AutoNLP", return_tensors="pt")
+
+outputs = model(**inputs)
+```

config.json

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+{
+  "_name_or_path": "AutoNLP",
+  "_num_labels": 7,
+  "architectures": [
+    "XLMRobertaForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "attention_window": [
+    512,
+    512,
+    512,
+    512,
+    512,
+    512,
+    512,
+    512,
+    512,
+    512,
+    512,
+    512
+  ],
+  "bos_token_id": 0,
+  "eos_token_id": 2,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "Claim",
+    "1": "Concluding Statement",
+    "2": "Counterclaim",
+    "3": "Evidence",
+    "4": "Lead",
+    "5": "Position",
+    "6": "Rebuttal"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "Claim": 0,
+    "Concluding Statement": 1,
+    "Counterclaim": 2,
+    "Evidence": 3,
+    "Lead": 4,
+    "Position": 5,
+    "Rebuttal": 6
+  },
+  "layer_norm_eps": 1e-05,
+  "max_length": 128,
+  "max_position_embeddings": 4098,
+  "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",
+  "problem_type": "single_label_classification",
+  "transformers_version": "4.8.0",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 250002
+}

pytorch_model.bin

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sample_input.pkl

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special_tokens_map.json

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+{"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "sep_token": "</s>", "pad_token": "<pad>", "cls_token": "<s>", "mask_token": "<mask>"}

tokenizer_config.json

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+{"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "model_max_length": 4096, "name_or_path": "AutoNLP", "special_tokens_map_file": "/root/.cache/huggingface/transformers/7c13b4818281d0113e4169c1186efa9b60d585b5a0352a0cf9ffea29c886fd84.0dc5b1041f62041ebbd23b1297f2f573769d5c97d8b7c28180ec86b8f6185aa8", "sp_model_kwargs": {}, "tokenizer_class": "XLMRobertaTokenizer"}