copy from autotrain

README.md

@@ -1,3 +1,52 @@
 ---
-license: apache-2.0
+tags: autotrain
+language: unk
+widget:
+- text: "I love AutoTrain 🤗"
+datasets:
+- rajistics/autotrain-data-auditor-sentiment
+co2_eq_emissions: 3.165771608457648
 ---
+
+# Model Trained Using AutoTrain
+
+- Problem type: Multi-class Classification
+- Model ID: 1167143226
+- CO2 Emissions (in grams): 3.165771608457648
+
+## Validation Metrics
+
+- Loss: 0.3418470025062561
+- Accuracy: 0.8617131062951496
+- Macro F1: 0.8448284352912685
+- Micro F1: 0.8617131062951496
+- Weighted F1: 0.8612696670395574
+- Macro Precision: 0.8440532616584138
+- Micro Precision: 0.8617131062951496
+- Weighted Precision: 0.8612762332366959
+- Macro Recall: 0.8461980005490884
+- Micro Recall: 0.8617131062951496
+- Weighted Recall: 0.8617131062951496
+
+
+## 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/rajistics/autotrain-auditor-sentiment-1167143226
+```
+
+Or Python API:
+
+```
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+
+model = AutoModelForSequenceClassification.from_pretrained("rajistics/autotrain-auditor-sentiment-1167143226", use_auth_token=True)
+
+tokenizer = AutoTokenizer.from_pretrained("rajistics/autotrain-auditor-sentiment-1167143226", 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": 3,
+  "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": "0",
+    "1": "1",
+    "2": "2"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2
+  },
+  "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": "4.20.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30873
+}

pytorch_model.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:2092476524bf609bfc3a5703076501e729f27435f51991e2105f272be7195853
+size 439087469

special_tokens_map.json

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

tokenizer_config.json

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