Commit From AutoTrain
Browse files- .gitattributes +3 -0
- README.md +46 -0
- config.json +44 -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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*.bin.* 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: autotrain
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language: en
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widget:
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- text: "I love AutoTrain 🤗"
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datasets:
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- BraveOni/autotrain-data-2ch-text-classification
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co2_eq_emissions: 0.08564281067919652
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---
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# Model Trained Using AutoTrain
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- Problem type: Binary Classification
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- Model ID: 955631800
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- CO2 Emissions (in grams): 0.08564281067919652
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## Validation Metrics
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- Loss: 0.34108611941337585
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- Accuracy: 0.8671983356449375
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- Precision: 0.7883283877349159
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- Recall: 0.8250517598343685
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- AUC: 0.9236450689447471
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- F1: 0.8062721294891249
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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 AutoTrain"}' https://api-inference.huggingface.co/models/BraveOni/autotrain-2ch-text-classification-955631800
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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("BraveOni/autotrain-2ch-text-classification-955631800", use_auth_token=True)
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tokenizer = AutoTokenizer.from_pretrained("BraveOni/autotrain-2ch-text-classification-955631800", use_auth_token=True)
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inputs = tokenizer("I love AutoTrain", 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": "AutoTrain",
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"_num_labels": 2,
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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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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 1024,
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"id2label": {
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"0": "0.0",
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"1": "1.0"
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},
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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"label2id": {
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"0.0": 0,
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"1.0": 1
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},
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"layer_norm_eps": 1e-12,
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"max_length": 64,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 16,
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"num_hidden_layers": 24,
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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": 28996
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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:edb1fcdb4b77026207870129c30e997b3c7a29c4792a5c9d490bd818b9bc88a1
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size 1334486957
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sample_input.pkl
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version https://git-lfs.github.com/spec/v1
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oid sha256:4430482114ba0bf1fedee99f64da4b5a3376237d0146a24b25af5a407f75b912
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size 2848
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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": false, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 512, "special_tokens_map_file": null, "name_or_path": "AutoTrain", "tokenizer_class": "BertTokenizer"}
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vocab.txt
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