Commit From AutoNLP
Browse files- .gitattributes +2 -0
- README.md +52 -0
- config.json +98 -0
- pytorch_model.bin +3 -0
- sample_input.pkl +3 -0
- special_tokens_map.json +1 -0
- tokenizer.json +0 -0
- tokenizer_config.json +1 -0
- vocab.txt +0 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zstandard filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zstandard filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.tar.gz filter=lfs diff=lfs merge=lfs -text
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*.pkl filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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tags: autonlp
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language: zh
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widget:
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- text: "I love AutoNLP 🤗"
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datasets:
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- kyleinincubated/autonlp-data-cat333
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co2_eq_emissions: 2.267288583123193
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---
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# Model Trained Using AutoNLP
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- Problem type: Multi-class Classification
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- Model ID: 624217911
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- CO2 Emissions (in grams): 2.267288583123193
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## Validation Metrics
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- Loss: 0.39670249819755554
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- Accuracy: 0.9098901098901099
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- Macro F1: 0.7398394202169645
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- Micro F1: 0.9098901098901099
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- Weighted F1: 0.9073329464119164
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- Macro Precision: 0.7653753530396269
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- Micro Precision: 0.9098901098901099
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- Weighted Precision: 0.9096917983040914
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- Macro Recall: 0.7382843728794468
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- Micro Recall: 0.9098901098901099
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- Weighted Recall: 0.9098901098901099
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## Usage
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You can use cURL to access this model:
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```
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$ 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/kyleinincubated/autonlp-cat333-624217911
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```
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Or Python API:
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```
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from transformers import AutoModelForSequenceClassification, AutoTokenizer
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model = AutoModelForSequenceClassification.from_pretrained("kyleinincubated/autonlp-cat333-624217911", use_auth_token=True)
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tokenizer = AutoTokenizer.from_pretrained("kyleinincubated/autonlp-cat333-624217911", use_auth_token=True)
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inputs = tokenizer("I love AutoNLP", return_tensors="pt")
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outputs = model(**inputs)
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```
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config.json
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{
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"_name_or_path": "AutoNLP",
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"_num_labels": 29,
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"architectures": [
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"BertForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"classifier_dropout": null,
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"directionality": "bidi",
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "\u4e92\u8054\u7f51\u670d\u52a1",
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"1": "\u4ea4\u901a\u8fd0\u8f93",
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"2": "\u4f11\u95f2\u670d\u52a1",
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"3": "\u4f20\u5a92",
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"4": "\u4fe1\u606f\u6280\u672f",
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"5": "\u516c\u7528\u4e8b\u4e1a",
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"6": "\u519c\u4e1a",
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"7": "\u5316\u5de5\u5236\u9020",
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"8": "\u533b\u836f\u751f\u7269",
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"9": "\u5546\u4e1a\u8d38\u6613",
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"10": "\u5efa\u7b51\u4e1a",
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"11": "\u623f\u5730\u4ea7",
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"12": "\u6559\u80b2",
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"13": "\u6587\u5316",
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"14": "\u6709\u8272\u91d1\u5c5e",
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"15": "\u6797\u4e1a",
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"16": "\u6c7d\u8f66\u5236\u9020",
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"17": "\u6e14\u4e1a",
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"18": "\u7535\u5b50\u5236\u9020",
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"19": "\u7535\u6c14\u8bbe\u5907",
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"20": "\u755c\u7267\u4e1a",
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"21": "\u7eba\u7ec7\u670d\u88c5\u5236\u9020",
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"22": "\u8f7b\u5de5\u5236\u9020",
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"23": "\u901a\u4fe1",
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"24": "\u91c7\u77ff\u4e1a",
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"25": "\u94a2\u94c1",
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"26": "\u94f6\u884c",
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"27": "\u975e\u94f6\u91d1\u878d",
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"28": "\u98df\u54c1\u996e\u6599"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"\u4e92\u8054\u7f51\u670d\u52a1": 0,
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"\u4ea4\u901a\u8fd0\u8f93": 1,
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"\u4f20\u5a92": 3,
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"\u4fe1\u606f\u6280\u672f": 4,
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"\u516c\u7528\u4e8b\u4e1a": 5,
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"\u519c\u4e1a": 6,
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"\u5316\u5de5\u5236\u9020": 7,
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"\u533b\u836f\u751f\u7269": 8,
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"\u5546\u4e1a\u8d38\u6613": 9,
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"\u5efa\u7b51\u4e1a": 10,
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"\u623f\u5730\u4ea7": 11,
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"\u6559\u80b2": 12,
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"\u6587\u5316": 13,
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"\u6709\u8272\u91d1\u5c5e": 14,
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"\u6797\u4e1a": 15,
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"\u6c7d\u8f66\u5236\u9020": 16,
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"\u6e14\u4e1a": 17,
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"\u7535\u5b50\u5236\u9020": 18,
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"\u7535\u6c14\u8bbe\u5907": 19,
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"\u7eba\u7ec7\u670d\u88c5\u5236\u9020": 21,
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"\u8f7b\u5de5\u5236\u9020": 22,
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"\u901a\u4fe1": 23,
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"\u91c7\u77ff\u4e1a": 24,
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"\u94a2\u94c1": 25,
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"\u94f6\u884c": 26,
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"\u975e\u94f6\u91d1\u878d": 27,
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"\u98df\u54c1\u996e\u6599": 28
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},
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"layer_norm_eps": 1e-12,
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"max_length": 128,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"output_past": true,
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"pad_token_id": 0,
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"padding": "max_length",
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"pooler_fc_size": 768,
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"pooler_num_attention_heads": 12,
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"pooler_num_fc_layers": 3,
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"pooler_size_per_head": 128,
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"pooler_type": "first_token_transform",
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"torch_dtype": "float32",
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"transformers_version": "4.15.0",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 21128
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:3c2275cee1ee178e5782dba361dc802eb2d02e5cb18aa2939ab2e5df77bb51c2
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size 409243885
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sample_input.pkl
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version https://git-lfs.github.com/spec/v1
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oid sha256:af6126e4ca5275eecac76d46e73cb611feaded621de907507d23f8f153a9a44d
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size 4384
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special_tokens_map.json
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{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}
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tokenizer.json
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tokenizer_config.json
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{"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "special_tokens_map_file": "/root/.cache/huggingface/transformers/8183382ed1d3dbb68e827ee934b131f7a2fded38f6b5d6e94cf29c9e363e7cde.dd8bd9bfd3664b530ea4e645105f557769387b3da9f79bdb55ed556bdd80611d", "name_or_path": "AutoNLP", "tokenizer_class": "BertTokenizer"}
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vocab.txt
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