Commit From AutoNLP

README.md

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+---
+tags: autonlp
+language: bn
+widget:
+- text: "I love AutoNLP 🤗"
+datasets:
+- albertvillanova/autonlp-data-baselines-indic_glue-multi_class_classification
+---
+
+# Model Trained Using AutoNLP
+
+- Problem type: Multi-class Classification
+- Model ID: 1351187
+
+## Validation Metrics
+
+- Loss: 0.46760785579681396
+- Accuracy: 0.8412473423104181
+- Macro F1: 0.8151341402067301
+- Micro F1: 0.8412473423104181
+- Weighted F1: 0.8458231431392536
+- Macro Precision: 0.804355047657178
+- Micro Precision: 0.8412473423104181
+- Weighted Precision: 0.8606653801556983
+- Macro Recall: 0.8328042776824057
+- Micro Recall: 0.8412473423104181
+- Weighted Recall: 0.8412473423104181
+
+
+## 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/albertvillanova/autonlp-baselines-indic_glue-multi_class_classification-1351187
+```
+
+Or Python API:
+
+```
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+
+model = AutoModelForSequenceClassification.from_pretrained("albertvillanova/autonlp-baselines-indic_glue-multi_class_classification-1351187", use_auth_token=True)
+
+tokenizer = AutoTokenizer.from_pretrained("albertvillanova/autonlp-baselines-indic_glue-multi_class_classification-1351187", 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": 6,
+  "architectures": [
+    "AlbertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0,
+  "bos_token_id": 2,
+  "classifier_dropout_prob": 0.1,
+  "down_scale_factor": 1,
+  "embedding_size": 128,
+  "eos_token_id": 3,
+  "gap_size": 0,
+  "hidden_act": "gelu_new",
+  "hidden_dropout_prob": 0,
+  "hidden_size": 1024,
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5"
+  },
+  "initializer_range": 0.02,
+  "inner_group_num": 1,
+  "intermediate_size": 4096,
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5
+  },
+  "layer_norm_eps": 1e-12,
+  "max_length": 64,
+  "max_position_embeddings": 512,
+  "model_type": "albert",
+  "net_structure_type": 0,
+  "num_attention_heads": 16,
+  "num_hidden_groups": 1,
+  "num_hidden_layers": 24,
+  "num_memory_blocks": 0,
+  "pad_token_id": 0,
+  "padding": "max_length",
+  "position_embedding_type": "absolute",
+  "transformers_version": "4.5.1",
+  "type_vocab_size": 2,
+  "vocab_size": 32000
+}

pytorch_model.bin

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+oid sha256:61e8371df57f6d4a19d894cf5806b64b6cd1b9d987a79f2dec6633be1cd7c055
+size 71800683