Commit From AutoTrain
Browse files- .gitattributes +3 -0
- README.md +56 -0
- config.json +44 -0
- merges.txt +0 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +51 -0
- tokenizer.json +3 -0
- tokenizer_config.json +65 -0
- vocab.json +0 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst 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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*.zst 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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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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tags:
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- autotrain
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- text-classification
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language:
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- de
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widget:
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- text: "I love AutoTrain 🤗"
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datasets:
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- BIDEQUITY/autotrain-data-bidequity-page-classifier
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co2_eq_emissions:
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emissions: 1.316894718008702
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---
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# Model Trained Using AutoTrain
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- Problem type: Multi-class Classification
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- Model ID: 49442119390
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- CO2 Emissions (in grams): 1.3169
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## Validation Metrics
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- Loss: 0.416
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- Accuracy: 0.870
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- Macro F1: 0.781
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- Micro F1: 0.870
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- Weighted F1: 0.864
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- Macro Precision: 0.888
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- Micro Precision: 0.870
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- Weighted Precision: 0.878
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- Macro Recall: 0.752
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- Micro Recall: 0.870
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- Weighted Recall: 0.870
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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/BIDEQUITY/autotrain-bidequity-page-classifier-49442119390
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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("BIDEQUITY/autotrain-bidequity-page-classifier-49442119390", use_auth_token=True)
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tokenizer = AutoTokenizer.from_pretrained("BIDEQUITY/autotrain-bidequity-page-classifier-49442119390", 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": 4,
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"architectures": [
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"RobertaForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"bos_token_id": 0,
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"classifier_dropout": null,
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"eos_token_id": 2,
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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": 768,
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"id2label": {
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"0": "customer_reference",
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"1": "job_posting",
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"2": "other",
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"3": "partner_reference"
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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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"customer_reference": 0,
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"job_posting": 1,
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"other": 2,
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"partner_reference": 3
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},
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"layer_norm_eps": 1e-05,
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"max_length": 512,
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"max_position_embeddings": 514,
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"model_type": "roberta",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 1,
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"padding": "max_length",
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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": "4.25.1",
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 52009
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}
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merges.txt
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:1a6a84de903237a9bac0ea870b9a0d3cdcfb3b85f6d0c6f2bce4ce177a0f8df9
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size 504025781
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special_tokens_map.json
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{
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"pad_token": {
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}
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tokenizer.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:19a8333241d1e213f6e2016f8e3dd612255bacfafcea7d1b48ddeb9088fda856
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size 2308834
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tokenizer_config.json
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},
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"single_word": false
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},
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"special_tokens_map_file": null,
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"rstrip": false,
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"single_word": false
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}
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}
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vocab.json
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